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DBMS > CrateDB vs. HugeGraph vs. JanusGraph vs. Spark SQL

System Properties Comparison CrateDB vs. HugeGraph vs. JanusGraph vs. Spark SQL

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDistributed Database based on LuceneA fast-speed and highly-scalable Graph DBMSA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Spark SQL is a component on top of 'Spark Core' for structured data processing
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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecratedb.comgithub.com/­hugegraph
hugegraph.apache.org
janusgraph.orgspark.apache.org/­sql
Technical documentationcratedb.com/­docshugegraph.apache.org/­docsdocs.janusgraph.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCrateBaiduLinux Foundation; originally developed as Titan by AureliusApache Software Foundation
Initial release2013201820172014
Current release0.90.6.3, February 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0
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 languageJavaJavaJavaScala
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Unix
Linux
OS X
Unix
Windows
Linux
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.nononono
Secondary indexesyesyes infoalso supports composite index and range indexyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
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
Groovy
Java
Python
Clojure
Java
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions (Javascript)asynchronous Gremlin script jobsyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infodepending on used storage backend, e.g. Cassandra and HBaseyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparkyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphyes infoRelationships in graphsno
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 strategyACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlrights management via user accountsUsers, roles and permissionsUser authentification and security via Rexster Graph Serverno
More information provided by the system vendor
CrateDBHugeGraphJanusGraph infosuccessor of TitanSpark SQL
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
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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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CrateDBHugeGraphJanusGraph infosuccessor of TitanSpark SQL
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