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DBMS > Adabas vs. Apache Phoenix vs. Datomic vs. Google Cloud Datastore

System Properties Comparison Adabas vs. Apache Phoenix vs. Datomic vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformA scale-out RDBMS with evolutionary schema built on Apache HBaseDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelMultivalue DBMSRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.58
Rank#91  Overall
#1  Multivalue DBMS
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlphoenix.apache.orgwww.datomic.comcloud.google.com/­datastore
Technical documentationphoenix.apache.orgdocs.datomic.comcloud.google.com/­datastore/­docs
DeveloperSoftware AGApache Software FoundationCognitectGoogle
Initial release1971201420122008
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, Clojure
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
Linux
Unix
Windows
All OS with a Java VMhosted
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewayyesnoSQL-like query language (GQL)
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
JDBCRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesNaturalC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresin Naturaluser defined functionsyes infoTransaction Functionsusing Google App Engine
TriggersnonoBy using transaction functionsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual 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.
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
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 developmentno
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Adabas infodenotes "adaptable data base"Apache PhoenixDatomicGoogle Cloud Datastore
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