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Starcounter.MultiModelBenchmark

This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.

Setup

Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.

  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.

See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.

Test data

Benchmark

Starcounter.MultiModelBenchmark offers two benchmarking options.

1. Using Starcounter native C# language binding

In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server. Starcounter native applications have significant performance advantage over the traditional client-server network communication.

The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.

Use benchmark entry point to start required test. See the PostMan collection above.

2. Using HTTP REST API

In this mode, client is a classical REST API consumer.

Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.

Starcounter REST API NodeJs implementation is available in the scripts/description.js file. There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.

Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.

About

ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0

Topics

arangodbbenchmarkgraphgraph-databasemultimodelstarcounter

Resources

Readme
MIT license
Activity
Custom properties

Stars

1 star

Watchers

9 watching

Forks

1 fork
Report repository

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
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Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
About
ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
9 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
About
ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
9 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
About
ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
9 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
About
ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
9 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
About
ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
9 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
About
ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
9 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Starcounter.MultiModelBenchmark
This is an implementation of the open source ArangoDB's benchmark using Starcounter 3.0.
Setup
Starcounter.MultiModelBenchmark requires Starcounter 3.0 Alpha-20190930.
  • Clone the Starcounter.MultiModelBenchmark repository.
  • Create artifacts folder on the same level as Starcounter.MultiModelBenchmark folder.
  • Download the latest available Starcounter 3.0 from starcounter.io and unzip it into the artifacts folder.
  • Build Starcounter.MultiModelBenchmark with dotnet CLI or with Visual Studio 2019.
  • Download and unzip test data into a folder.
  • Start Starcounter.MultiModelBenchmark project with dotnet CLI or with Visual Studio 2019.
  • Create required database indexes using create-indexes end point.
  • Import test data using the import-profiles and import-relations end points.
See Starcounter.MultiModelBenchmark.postman_collection.jsonPostMan collection for the detailed REST API description.
Test data
Benchmark
Starcounter.MultiModelBenchmark offers two benchmarking options.
1. Using Starcounter native C# language binding
In this mode, client is a Starcounter native application with direct database access, which means that database (server) and application (client) reside on the same physical or virtual server.
Starcounter native applications have significant performance advantage over the traditional client-server network communication.
The benchmark payload is located in the data/data.zip archive, and has to be manually unzipped into the same folder prior to running any tests.
Use benchmark entry point to start required test. See the PostMan collection above.
2. Using HTTP REST API
In this mode, client is a classical REST API consumer.
Use ArangoDB NodeJs benchmarking suite to run the tests and collect results.
Starcounter REST API NodeJs implementation is available in the scripts/description.js file.
There is also an sh script to perform all the benchmarks using ArangoDB's NodeJs benchmarker - scripts/.
Note: NodeJs consumes a lot of RAM when performing multiple parallel HTTP requests, it might be required to manually increase available amount of RAM for the NodeJs process.
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ArangoDB's NoSQL Performance Benchmark using Starcounter 3.0
Topics
arangodbbenchmarkgraphgraph-databasemultimodelstarcounter
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