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DBMS > AnzoGraph DB vs. Datomic vs. GridGain vs. SAP SQL Anywhere vs. Splice Machine

System Properties Comparison AnzoGraph DB vs. Datomic vs. GridGain vs. SAP SQL Anywhere vs. Splice Machine

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonDatomic  Xexclude from comparisonGridGain  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGridGain is an in-memory computing platform, built on Apache IgniteRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score4.25
Rank#79  Overall
#43  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.datomic.comwww.gridgain.comwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlsplicemachine.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.datomic.comwww.gridgain.com/­docs/­index.htmlhelp.sap.com/­docs/­SAP_SQL_Anywheresplicemachine.com/­how-it-works
DeveloperCambridge SemanticsCognitectGridGain Systems, Inc.SAP infoformerly SybaseSplice Machine
Initial release20182012200719922014
Current release2.3, January 20211.0.6735, June 2023GridGain 8.5.117, July 20153.1, March 2021
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infolimited edition freecommercialcommercialOpen 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 languageJava, ClojureJava, C++, .NetJava
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesyes
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.nonoyesyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noANSI-99 for query and DML statements, subset of DDLyesyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
RESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
Python
Clojure
Java
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsyes (compute grid and cache interceptors can be used instead)yes, in C/C++, Java, .Net or Perlyes infoJava
TriggersnoBy using transaction functionsyes (cache interceptors and events)yesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnone infoBut extensive use of caching in the application peersShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusternone infoBut extensive use of caching in the application peersyes (replicated cache)Source-replica replication infoDatabase mirroringMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes (compute grid and hadoop accelerator)noYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesyesyes
User concepts infoAccess controlAccess rights for users and rolesnoSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
AnzoGraph DBDatomicGridGainSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSplice Machine
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