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DBMS > CrateDB vs. Hive vs. Linter vs. OpenEdge

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

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHive  Xexclude from comparisonLinter  Xexclude from comparisonOpenEdge  Xexclude from comparison
DescriptionDistributed Database based on Lucenedata warehouse software for querying and managing large distributed datasets, built on HadoopRDBMS for high security requirementsApplication development environment with integrated database management system
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score3.51
Rank#86  Overall
#46  Relational DBMS
Websitecratedb.comhive.apache.orglinter.ruwww.progress.com/­openedge
Technical documentationcratedb.com/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperCrateApache Software Foundation infoinitially developed by Facebookrelex.ruProgress Software Corporation
Initial release2013201219901984
Current release3.1.3, April 2022OpenEdge 12.2, March 2020
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2commercialcommercial
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 languageJavaJavaC and 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
AIX
HP-UX
Linux
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsyesyes infoclose to SQL 92
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)
JDBC
ODBC
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
Progress proprietary ABL (Advanced Business Language)
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/SQLyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning infosince Version 11.4
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelselectable replication factorSource-replica replicationSource-replica replication
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 ConsistencyImmediate 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 strategynoACIDACID
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 controlrights management via user accountsAccess rights for users, groups and rolesfine grained access rights according to SQL-standardUsers and groups
More information provided by the system vendor
CrateDBHiveLinterOpenEdge
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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CrateDBHiveLinterOpenEdge
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