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DBMS > Alibaba Cloud Table Store vs. CrateDB vs. MonetDB vs. ToroDB

System Properties Comparison Alibaba Cloud Table Store vs. CrateDB vs. MonetDB vs. ToroDB

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Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonCrateDB  Xexclude from comparisonMonetDB  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA fully managed Wide Column Store for large quantities of semi-structured data with real-time accessDistributed Database based on LuceneA relational database management system that stores data in columnsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelWide column storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSDocument store
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.24
Rank#310  Overall
#12  Wide column stores
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.72
Rank#148  Overall
#68  Relational DBMS
Websitewww.alibabacloud.com/­product/­table-storecratedb.comwww.monetdb.orggithub.com/­torodb/­server
Technical documentationwww.alibabacloud.com/­help/­en/­tablestorecratedb.com/­docswww.monetdb.org/­Documentation
DeveloperAlibabaCrateMonetDB BV8Kdata
Initial release2016201320042016
Current releaseDec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoMozilla Public License 2.0Open Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaCJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
Solaris
Windows
All OS with a Java 7 VM
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infostring, integer, double, boolean, date, object_id
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 indexesnoyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyes infoSQL 2003 with some extensions
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesJava
Python
.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
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes, in SQL, C, R
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingSharding via remote tablesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceConfigurable replication on table/partition-levelnone infoSource-replica replication available in experimental statusSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
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.nono
User concepts infoAccess controlAccess rights based on subaccounts and tokensrights management via user accountsfine grained access rights according to SQL-standardAccess rights for users and roles
More information provided by the system vendor
Alibaba Cloud Table StoreCrateDBMonetDBToroDB
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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More resources
Alibaba Cloud Table StoreCrateDBMonetDBToroDB
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