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DBMS > Blazegraph vs. Dragonfly vs. Vitess

System Properties Comparison Blazegraph vs. Dragonfly vs. Vitess

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonDragonfly  Xexclude from comparisonVitess  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#217  Overall
#19  Graph DBMS
#8  RDF stores
Score0.44
Rank#255  Overall
#38  Key-value stores
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websiteblazegraph.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
vitess.io
Technical documentationwiki.blazegraph.comwww.dragonflydb.io/­docsvitess.io/­docs
DeveloperBlazegraphDragonflyDB team and community contributorsThe Linux Foundation, PlanetScale
Initial release200620232013
Current release2.1.5, March 20191.0, March 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoBSL 1.1Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Go
Server operating systemsLinux
OS X
Windows
LinuxDocker
Linux
macOS
Data schemeschema-freescheme-freeyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesstrings, hashes, lists, sets, sorted sets, bit arraysyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesyesnoyes
SQL infoSupport of SQLSPARQL is used as query languagenoyes infowith proprietary extensions
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Proprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesLuayes infoproprietary syntax
Triggersnopublish/subscribe channels provide some trigger functionalityyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infoRelationships in Graphsnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Password-based authenticationUsers with fine-grained authorization concept infono user groups or roles

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More resources
BlazegraphDragonflyVitess
Recent citations in the news

Video: Blazegraph Accelerates Graph Computing with GPUs
20 December 2015, insideHPC

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

provided by Google News

DragonflyDB Announces $21m in New Funding and General Availability
21 March 2023, Business Wire

DragonflyDB reels in $21M for its speedy in-memory database
21 March 2023, SiliconANGLE News

DragonflyDB Raises $21M in Funding
21 March 2023, FinSMEs

Intel Linux Kernel Optimizations Show Huge Benefit For High Core Count Servers
29 March 2023, Phoronix

SFU Computing Science researchers receive 2022 ACM SIGMOD Research Highlight Award.
24 February 2023, Simon Fraser University News

provided by Google News

Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era
20 May 2024, InfoQ.com

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

CNCF’s Vitess Scales MySQL with the Help of Kubernetes
9 February 2018, The New Stack

provided by Google News



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