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DBMS > CrateDB vs. EsgynDB vs. Greenplum vs. Hive

System Properties Comparison CrateDB vs. EsgynDB vs. Greenplum vs. Hive

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGreenplum  Xexclude from comparisonHive  Xexclude from comparison
DescriptionDistributed Database based on LuceneEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitecratedb.comwww.esgyn.cngreenplum.orghive.apache.org
Technical documentationcratedb.com/­docsdocs.greenplum.orgcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperCrateEsgynPivotal Software Inc.Apache Software Foundation infoinitially developed by Facebook
Initial release2013201520052012
Current release7.0.0, September 20233.1.3, April 2022
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2
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++, JavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinuxAll OS with a Java VM
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 infosince Version 4.2
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Thrift
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
All languages supporting JDBC/ODBC/ADO.NetC
Java
Perl
Python
R
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)Java Stored Proceduresyesyes infouser defined functions and integration of map-reduce
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication between multi datacentersSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesno
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 strategyACIDACIDno
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.nonono
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles
More information provided by the system vendor
CrateDBEsgynDBGreenplumHive
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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CrateDBEsgynDBGreenplumHive
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