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DBMS > CrateDB vs. Hive vs. NSDb vs. OrigoDB

System Properties Comparison CrateDB vs. Hive vs. NSDb vs. OrigoDB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHive  Xexclude from comparisonNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionDistributed Database based on Lucenedata warehouse software for querying and managing large distributed datasets, built on HadoopScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA fully ACID in-memory object graph database
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSTime Series DBMSDocument store
Object oriented DBMS
Secondary database modelsRelational 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
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websitecratedb.comhive.apache.orgnsdb.ioorigodb.com
Technical documentationcratedb.com/­docscwiki.apache.org/­confluence/­display/­Hive/­Homensdb.io/­Architectureorigodb.com/­docs
DeveloperCrateApache Software Foundation infoinitially developed by FacebookRobert Friberg et al
Initial release2013201220172009 infounder the name LiveDB
Current release3.1.3, April 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source
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 languageJavaJavaJava, ScalaC#
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
macOS
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringUser defined using .NET types and collections
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 infocan be achieved using .NET
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Thrift
gRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
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
Java
Scala
.Net
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infouser defined functions and integration of map-reducenoyes
Triggersnonoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelselectable replication factorSource-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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynononodepending on model
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 strategynonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and rolesRole based authorization
More information provided by the system vendor
CrateDBHiveNSDbOrigoDB
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
CrateDBHiveNSDbOrigoDB
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