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DBMS > etcd vs. HBase vs. Riak KV vs. TimescaleDB

System Properties Comparison etcd vs. HBase vs. Riak KV vs. TimescaleDB

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonHBase  Xexclude from comparisonRiak KV  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableDistributed, fault tolerant key-value storeA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeWide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.64
Rank#54  Overall
#5  Key-value stores
Score31.25
Rank#26  Overall
#2  Wide column stores
Score4.44
Rank#80  Overall
#9  Key-value stores
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
hbase.apache.orgwww.timescale.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetOpenSource, formerly Basho TechnologiesTimescale
Initial release200820092017
Current release3.4, August 20192.3.4, January 20213.2.0, December 20222.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
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.
Implementation languageGoJavaErlangC
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesnonorestrictedyes
SQL infoSupport of SQLnononoyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
HTTP API
Native Erlang Interface
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavaErlanguser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes, watching key changesyesyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACID
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.noyesno
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes, using Riak Securityfine grained access rights according to SQL-standard

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etcdHBaseRiak KVTimescaleDB
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