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DBMS > Badger vs. Blazegraph vs. Spark SQL vs. TigerGraph

System Properties Comparison Badger vs. Blazegraph vs. Spark SQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBlazegraph  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Spark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelKey-value storeGraph DBMS
RDF store
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websitegithub.com/­dgraph-io/­badgerblazegraph.comspark.apache.org/­sqlwww.tigergraph.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwiki.blazegraph.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperDGraph LabsBlazegraphApache Software Foundation
Initial release2017200620142017
Current release2.1.5, March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoextended commercial license availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaScalaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes infoRDF literal typesyesyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLnoSPARQL is used as query languageSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesGo.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoyesnoyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoRelationships in Graphsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnoSecurity and Authentication via Web Application Container (Tomcat, Jetty)noRole-based access control

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More resources
BadgerBlazegraphSpark SQLTigerGraph
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