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DBMS > Adabas vs. AnzoGraph DB vs. Datomic vs. Graph Engine vs. Spark SQL

System Properties Comparison Adabas vs. AnzoGraph DB vs. Datomic vs. Graph Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonDatomic  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformScalable 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 durabilityA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelMultivalue DBMSGraph DBMS
RDF store
Relational DBMSGraph DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.58
Rank#91  Overall
#1  Multivalue DBMS
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score0.62
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcambridgesemantics.com/­anzographwww.datomic.comwww.graphengine.iospark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.datomic.comwww.graphengine.io/­docs/­manualspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftware AGCambridge SemanticsCognitectMicrosoftApache Software Foundation
Initial release19712018201220102014
Current release2.3, January 20211.0.6735, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availablecommercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, Clojure.NET and CScala
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxAll OS with a Java VM.NETLinux
OS X
Windows
Data schemeyesSchema-free and OWL/RDFS-schema supportyesyesyes
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.nonononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySPARQL and SPARQL* as primary query language. Cypher preview.nonoSQL-like DML and DDL statements
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Supported programming languagesNaturalC++
Java
Python
Clojure
Java
C#
C++
F#
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresin Naturaluser defined functions and aggregatesyes infoTransaction Functionsyesno
TriggersnonoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaAutomatic shardingnone infoBut extensive use of caching in the application peershorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorMulti-source replication in MPP-Clusternone infoBut extensive use of caching in the application peersnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate Consistency
Foreign keys infoReferential integritynono infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)Access rights for users and rolesnono

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More resources
Adabas infodenotes "adaptable data base"AnzoGraph DBDatomicGraph Engine infoformer name: TrinitySpark SQL
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