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DBMS > Apache Druid vs. CrateDB vs. Hive vs. SwayDB

System Properties Comparison Apache Druid vs. CrateDB vs. Hive vs. SwayDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCrateDB  Xexclude from comparisonHive  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Database based on Lucenedata warehouse software for querying and managing large distributed datasets, built on HadoopAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score0.76
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#18  Time Series DBMS
#8  Vector DBMS
Score64.82
Rank#18  Overall
#12  Relational DBMS
Score0.03
Rank#385  Overall
#60  Key-value stores
Websitedruid.apache.orgcratedb.comhive.apache.orgswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designcratedb.com/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation and contributorsCrateApache Software Foundation infoinitially developed by FacebookSimer Plaha
Initial release2012201320122018
Current release29.0.0, February 20243.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open SourceOpen Source infoApache Version 2Open Source infoGNU Affero GPL V3.0
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 languageJavaJavaJavaScala
Server operating systemsLinux
OS X
Unix
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VM
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.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
Kotlin
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes infouser defined functions and integration of map-reduceno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesConfigurable replication on table/partition-levelselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategynoAtomic execution of operations
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemrights management via user accountsAccess rights for users, groups and rolesno
More information provided by the system vendor
Apache DruidCrateDBHiveSwayDB
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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Apache DruidCrateDBHiveSwayDB
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