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DBMS > CrateDB vs. Hive vs. Linter vs. Rockset

System Properties Comparison CrateDB vs. Hive vs. Linter vs. Rockset

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHive  Xexclude from comparisonLinter  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionDistributed Database based on Lucenedata warehouse software for querying and managing large distributed datasets, built on HadoopRDBMS for high security requirementsA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSDocument store
Secondary database modelsRelational DBMSSpatial DBMSRelational DBMS
Search engine
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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitecratedb.comhive.apache.orglinter.rurockset.com
Technical documentationcratedb.com/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.rockset.com
DeveloperCrateApache Software Foundation infoinitially developed by Facebookrelex.ruRockset
Initial release2013201219902019
Current release3.1.3, April 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
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 languageJavaJavaC and C++C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesdynamic typing
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 infoingestion from XML files supported
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsyesRead-only SQL queries, including JOINs
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
HTTP REST
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
PHP
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infouser defined functions and integration of map-reduceyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelselectable replication factorSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
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 strategynoACIDno
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.no
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAccess rights for users and organizations can be defined via Rockset console
More information provided by the system vendor
CrateDBHiveLinterRockset
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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CrateDBHiveLinterRockset
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