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

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

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 comparisonYottaDB  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 fast and solid embedded Key-value store
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS infousing the Octo plugin
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
Score0.28
Rank#306  Overall
#44  Key-value stores
Websiteetcd.io
github.com/­etcd-io/­etcd
www.kinetica.comwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlsplicemachine.comyottadb.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-worksyottadb.com/­resources/­documentation
DeveloperKineticaSAP infoformerly SybaseSplice MachineYottaDB, LLC
Initial release2012199220142001
Current release3.4, August 20197.1, August 202117, July 20153.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL 3.0
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
Docker
Linux
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesno
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.nonoyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyesby using the Octo plugin
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
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
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresnouser defined functionsyes, in C/C++, Java, .Net or Perlyes infoJava
Triggersyes, watching key changesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
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
yes
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 Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 RAMyesyesyes
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-standardUsers and groups based on OS-security mechanisms

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More resources
etcdKineticaSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSplice MachineYottaDB
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