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DBMS > CrateDB vs. JanusGraph vs. TigerGraph vs. Valentina Server

System Properties Comparison CrateDB vs. JanusGraph vs. TigerGraph vs. Valentina Server

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonTigerGraph  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionDistributed Database based on LuceneA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeObject-relational database and reports server
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMSGraph DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitecratedb.comjanusgraph.orgwww.tigergraph.comwww.valentina-db.net
Technical documentationcratedb.com/­docsdocs.janusgraph.orgdocs.tigergraph.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCrateLinux Foundation; originally developed as Titan by AureliusParadigma Software
Initial release2013201720171999
Current release0.6.3, February 20235.7.5
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Unix
Windows
LinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query language (GSQL)yes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ODBC
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Clojure
Java
Python
C++
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesyesyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Faunus, a graph analytics engineyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlrights management via user accountsUser authentification and security via Rexster Graph ServerRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
CrateDBJanusGraph infosuccessor of TitanTigerGraphValentina Server
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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CrateDBJanusGraph infosuccessor of TitanTigerGraphValentina Server
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