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DBMS > Adabas vs. EsgynDB vs. Google Cloud Datastore vs. KairosDB vs. RDF4J

System Properties Comparison Adabas vs. EsgynDB vs. Google Cloud Datastore vs. KairosDB vs. RDF4J

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKairosDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Time Series DBMS based on Cassandra or H2RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelMultivalue DBMSRelational DBMSDocument storeTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.62
Rank#239  Overall
#20  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlwww.esgyn.cncloud.google.com/­datastoregithub.com/­kairosdb/­kairosdbrdf4j.org
Technical documentationcloud.google.com/­datastore/­docskairosdb.github.iordf4j.org/­documentation
DeveloperSoftware AGEsgynGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release19712015200820132004
Current release1.2.2, November 2018
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaJava
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxhostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewayyesSQL-like query language (GQL)nono
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Graphite protocol
HTTP REST
Telnet API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesNaturalAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript infoNode.js
PHP
Python
Java
PHP
Python
Server-side scripts infoStored proceduresin NaturalJava Stored Proceduresusing Google App Enginenoyes
TriggersnonoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingShardingSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorMulti-source replication between multi datacentersMulti-source replication using Paxosselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)fine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access controlno

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More resources
Adabas infodenotes "adaptable data base"EsgynDBGoogle Cloud DatastoreKairosDBRDF4J infoformerly known as Sesame
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