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DBMS > etcd vs. Kinetica vs. SAP SQL Anywhere vs. Splice Machine vs. TimescaleDB

System Properties Comparison etcd vs. Kinetica vs. SAP SQL Anywhere vs. Splice Machine vs. TimescaleDB

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonKinetica  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed reliable key-value storeFully vectorized database across both GPUs and CPUsRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.kinetica.comwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlsplicemachine.comwww.timescale.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.kinetica.comhelp.sap.com/­docs/­SAP_SQL_Anywheresplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperKineticaSAP infoformerly SybaseSplice MachineTimescale
Initial release2012199220142017
Current release3.4, August 20197.1, August 202117, July 20153.1, March 20212.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, C++JavaC
Server operating systemsFreeBSD
Linux
Windows infoexperimental
LinuxAIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesnumerics, 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.nonoyesyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
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++
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functionsyes, in C/C++, Java, .Net or Perlyes infoJavauser 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 changesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioningyes, 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.Source-replica replicationSource-replica replication infoDatabase mirroringMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyesyesno
User concepts infoAccess controlnoAccess rights for users and roles on table levelfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
etcdKineticaSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSplice MachineTimescaleDB
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