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DBMS > Adabas vs. CrateDB vs. Spark SQL vs. Transwarp StellarDB

System Properties Comparison Adabas vs. CrateDB vs. Spark SQL vs. Transwarp StellarDB

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonCrateDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformDistributed Database based on LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingA distributed graph DBMS built for enterprise-level graph applications
Primary database modelMultivalue DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.79
Rank#102  Overall
#2  Multivalue DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#371  Overall
#39  Graph DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcratedb.comspark.apache.org/­sqlwww.transwarp.cn/­en/­product/­stellardb
Technical documentationcratedb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftware AGCrateApache Software FoundationTranswarp
Initial release197120132014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaScala
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewayyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsSQL-like query language
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
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
OpenCypher
Supported programming languagesNatural.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Java
Python
R
Scala
Server-side scripts infoStored proceduresin Naturaluser defined functions (Javascript)no
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorConfigurable replication on table/partition-levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno
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.nonono
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)rights management via user accountsnoyes
More information provided by the system vendor
Adabas infodenotes "adaptable data base"CrateDBSpark SQLTranswarp StellarDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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Adabas infodenotes "adaptable data base"CrateDBSpark SQLTranswarp StellarDB
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