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DBMS > Adabas vs. CrateDB vs. Microsoft Azure Table Storage vs. RocksDB

System Properties Comparison Adabas vs. CrateDB vs. Microsoft Azure Table Storage vs. RocksDB

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonCrateDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformDistributed Database based on LuceneA Wide Column Store for rapid development using massive semi-structured datasetsEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelMultivalue DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeKey-value store
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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.65
Rank#85  Overall
#11  Key-value stores
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlcratedb.comazure.microsoft.com/­en-us/­services/­storage/­tablesrocksdb.org
Technical documentationcratedb.com/­docsgithub.com/­facebook/­rocksdb/­wiki
DeveloperSoftware AGCrateMicrosoftFacebook, Inc.
Initial release1971201320122013
Current release8.11.4, April 2024
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesno
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 languageJavaC++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnono
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewayyes, but no triggers and constraints, and PostgreSQL compatibilitynono
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
RESTful HTTP APIC++ API
Java API
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
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresin Naturaluser defined functions (Javascript)nono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event ReplicatorConfigurable replication on table/partition-levelyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
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
Immediate Consistency
Foreign keys infoReferential integritynononono
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 strategyoptimistic lockingyes
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.nononoyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)rights management via user accountsAccess rights based on private key authentication or shared access signaturesno
More information provided by the system vendor
Adabas infodenotes "adaptable data base"CrateDBMicrosoft Azure Table StorageRocksDB
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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3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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Adabas infodenotes "adaptable data base"CrateDBMicrosoft Azure Table StorageRocksDB
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