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DBMS > CrateDB vs. Hypertable vs. Kinetica vs. Sadas Engine

System Properties Comparison CrateDB vs. Hypertable vs. Kinetica vs. Sadas Engine

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonSadas Engine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneAn open source BigTable implementation based on distributed file systems such as HadoopFully vectorized database across both GPUs and CPUsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitecratedb.comwww.kinetica.comwww.sadasengine.com
Technical documentationcratedb.com/­docsdocs.kinetica.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperCrateHypertable Inc.KineticaSADAS s.r.l.
Initial release2013200920122006
Current release0.9.8.11, March 20167.1, August 20218.0
License infoCommercial or Open SourceOpen SourceOpen Source infoGNU version 3. Commercial license availablecommercialcommercial infofree trial version available
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 languageJavaC++C, C++C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Windows infoan inofficial Windows port is available
LinuxAIX
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languages.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++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)nouser defined functionsno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelselectable replication factor on file system levelSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynono
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.noyes infoGPU vRAM or System RAMyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlrights management via user accountsnoAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
CrateDBHypertableKineticaSadas Engine
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
CrateDBHypertableKineticaSadas Engine
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