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DBMS > Amazon Redshift vs. Apache Druid vs. Kinetica vs. Warp 10

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Kinetica vs. Warp 10

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Druid  Xexclude from comparisonKinetica  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFully vectorized database across both GPUs and CPUsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteaws.amazon.com/­redshiftdruid.apache.orgwww.kinetica.comwww.warp10.io
Technical documentationdocs.aws.amazon.com/­redshiftdruid.apache.org/­docs/­latest/­designdocs.kinetica.comwww.warp10.io/­content/­02_Getting_started
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation and contributorsKineticaSenX
Initial release2012201220122015
Current release29.0.1, April 20247.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC, C++Java
Server operating systemshostedLinux
OS X
Unix
LinuxLinux
OS X
Windows
Data schemeyesyes infoschema-less columns are supportedyesschema-free
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.nononono
Secondary indexesrestrictedyesyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL for queryingSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
JDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnouser defined functionsyes infoWarpScript
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infomanual/auto, time-basedShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, via HDFS, S3 or other storage enginesSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.yesnoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles on table levelMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Amazon RedshiftApache DruidKineticaWarp 10
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