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DBMS > Adabas vs. AnzoGraph DB vs. Apache Impala vs. Google Cloud Datastore

System Properties Comparison Adabas vs. AnzoGraph DB vs. Apache Impala vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Datastore  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 virtualizationAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelMultivalue DBMSGraph DBMS
RDF store
Relational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.64
Rank#104  Overall
#1  Multivalue DBMS
Score0.22
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcambridgesemantics.com/­anzographimpala.apache.orgcloud.google.com/­datastore
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docs
DeveloperSoftware AGCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogle
Initial release1971201820132008
Current release2.3, January 20214.1.0, June 2022
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache Version 2commercial
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 languageC++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxLinuxhosted
Data schemeyesSchema-free and OWL/RDFS-schema supportyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, 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 indexesyesnoyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsSQL-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
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesNaturalC++
Java
Python
All languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresin Naturaluser defined functions and aggregatesyes infouser defined functions and integration of map-reduceusing Google App Engine
TriggersnononoCallbacks 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 VistaAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorMulti-source replication in MPP-Clusterselectable replication factorMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingyes infoquery execution via MapReduceyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterEventual 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 integritynono infonot needed in graphsnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)Access rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess 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"AnzoGraph DBApache ImpalaGoogle Cloud Datastore
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