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DBMS > Amazon Redshift vs. HBase vs. JanusGraph vs. Riak KV

System Properties Comparison Amazon Redshift vs. HBase vs. JanusGraph vs. Riak KV

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonHBase  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsWide-column store based on Apache Hadoop and on concepts of BigTableA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Distributed, fault tolerant key-value store
Primary database modelRelational DBMSWide column storeGraph DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteaws.amazon.com/­redshifthbase.apache.orgjanusgraph.org
Technical documentationdocs.aws.amazon.com/­redshifthbase.apache.org/­book.htmldocs.janusgraph.orgwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoApache top-level project, originally developed by PowersetLinux Foundation; originally developed as Titan by AureliusOpenSource, formerly Basho Technologies
Initial release2012200820172009
Current release2.3.4, January 20210.6.3, February 20233.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJavaErlang
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Unix
Windows
Linux
OS X
Data schemeyesschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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 indexesrestrictednoyesrestricted
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardnonono
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
Thrift
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Groovy
Java
PHP
Python
Scala
Clojure
Java
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infoCoprocessors in JavayesErlang
Triggersnoyesyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Faunus, a graph analytics engineyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyes infoRelationships in graphsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUser authentification and security via Rexster Graph Serveryes, using Riak Security

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More resources
Amazon RedshiftHBaseJanusGraph infosuccessor of TitanRiak KV
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