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DBMS > Amazon Redshift vs. Hive vs. KeyDB vs. Splice Machine

System Properties Comparison Amazon Redshift vs. Hive vs. KeyDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonHive  Xexclude from comparisonKeyDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsdata warehouse software for querying and managing large distributed datasets, built on HadoopAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­redshifthive.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
splicemachine.com
Technical documentationdocs.aws.amazon.com/­redshiftcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.keydb.devsplicemachine.com/­how-it-works
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoinitially developed by FacebookEQ Alpha Technology Ltd.Splice Machine
Initial release2012201220192014
Current release3.1.3, April 20223.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoBSD-3Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++Java
Server operating systemshostedAll OS with a Java VMLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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.nono
Secondary indexesrestrictedyesyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Thrift
Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
PHP
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infouser defined functions and integration of map-reduceLuayes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolessimple password-based access control and ACLAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon RedshiftHiveKeyDBSplice Machine
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