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DBMS > Amazon Redshift vs. Datomic vs. Kinetica vs. NSDb vs. Splice Machine

System Properties Comparison Amazon Redshift vs. Datomic vs. Kinetica vs. NSDb vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatomic  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.datomic.comwww.kinetica.comnsdb.iosplicemachine.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.datomic.comdocs.kinetica.comnsdb.io/­Architecturesplicemachine.com/­how-it-works
DeveloperAmazon (based on PostgreSQL)CognitectKineticaSplice Machine
Initial release20122012201220172014
Current release1.0.6735, June 20237.1, August 20213.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ClojureC, C++Java, ScalaJava
Server operating systemshostedAll OS with a Java VMLinuxLinux
macOS
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, stringyes
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 indexesrestrictedyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardnoSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C++
Java
JavaScript (Node.js)
Python
Java
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infoTransaction Functionsuser defined functionsnoyes infoJava
TriggersnoBy using transaction functionsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon RedshiftDatomicKineticaNSDbSplice Machine
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