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DBMS > AnzoGraph DB vs. IRONdb vs. JaguarDB vs. OushuDB vs. Splice Machine

System Properties Comparison AnzoGraph DB vs. IRONdb vs. JaguarDB vs. OushuDB vs. Splice Machine

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonIRONdb  Xexclude from comparisonJaguarDB  Xexclude from comparisonOushuDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityPerformant, highly scalable DBMS for AI and IoT applicationsA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Time Series DBMSKey-value store
Vector DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.circonus.com/solutions/time-series-database/www.jaguardb.comwww.oushu.com/­product/­oushuDBsplicemachine.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.circonus.com/irondb/category/getting-startedwww.jaguardb.com/­support.htmlwww.oushu.com/­documentationsplicemachine.com/­how-it-works
DeveloperCambridge SemanticsCirconus LLC.DataJaguar, Inc.OushuSplice Machine
Initial release2018201720152014
Current release2.3, January 2021V0.10.20, January 20183.3 July 20234.0.1, August 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialOpen Source infoGPL V3.0commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++ infothe server part. Clients available in other languagesJava
Server operating systemsLinuxLinuxLinuxLinuxLinux
OS X
Solaris
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsyesyesyes
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 indexesnonoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (Circonus Analytics Query Language: CAQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersFull-featured ANSI SQL supportyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
HTTP APIJDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes, in Luanoyesyes infoJava
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingAutomatic, metric affinity per nodeShardingyesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterconfigurable replication factor, datacenter awareMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnonoHadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate consistency per node, eventual consistency across nodesEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess rights for users and rolesnorights management via user accountsKerberos, SSL and role based accessAccess rights for users, groups and roles according to SQL-standard

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More resources
AnzoGraph DBIRONdbJaguarDBOushuDBSplice Machine
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