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DBMS > Adabas vs. CrateDB vs. RisingWave vs. Valentina Server

System Properties Comparison Adabas vs. CrateDB vs. RisingWave vs. Valentina Server

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonCrateDB  Xexclude from comparisonRisingWave  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformDistributed Database based on LuceneA distributed RDBMS for stream processing, wire-compatible with PostgreSQLObject-relational database and reports server
Primary database modelMultivalue DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.58
Rank#242  Overall
#111  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcratedb.comwww.risingwave.com/­databasewww.valentina-db.net
Technical documentationcratedb.com/­docsdocs.risingwave.com/­docs/­current/­introvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperSoftware AGCrateRisingWave LabsParadigma Software
Initial release1971201320221999
Current release1.2, September 20235.7.5
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 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 languageJavaRust
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportDocker
Linux
macOS
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesStandard SQL-types and JSONyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewayyes, but no triggers and constraints, and PostgreSQL compatibilityyesyes
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
PostgreSQL wire protocol
ODBC
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
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresin Naturaluser defined functions (Javascript)UDFs in Python or Javayes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorConfigurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynononoyes
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 datayesyes
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.nonoyesyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)rights management via user accountsUsers and Rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
Adabas infodenotes "adaptable data base"CrateDBRisingWaveValentina Server
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"CrateDBRisingWaveValentina Server
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