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DBMS > Apache IoTDB vs. etcd vs. IRONdb vs. Kinetica vs. SAP SQL Anywhere

System Properties Comparison Apache IoTDB vs. etcd vs. IRONdb vs. Kinetica vs. SAP SQL Anywhere

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonetcd  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed reliable key-value storeA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelTime Series DBMSKey-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
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
Websiteiotdb.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.circonus.com/solutions/time-series-database/www.kinetica.comwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.circonus.com/irondb/category/getting-starteddocs.kinetica.comhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperApache Software FoundationCirconus LLC.KineticaSAP infoformerly Sybase
Initial release2018201720121992
Current release1.1.0, April 20233.4, August 2019V0.10.20, January 20187.1, August 202117, July 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialcommercialcommercial
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 languageJavaGoC and C++C, C++
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
Windows infoexperimental
LinuxLinuxAIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes infotext, numeric, histogramsyesyes
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.nonononoyes
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
Native API
gRPC
JSON over HTTP
HTTP APIJDBC
ODBC
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoyes, in Luauser defined functionsyes, in C/C++, Java, .Net or Perl
Triggersyesyes, watching key changesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodeShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.configurable replication factor, datacenter awareSource-replica replicationSource-replica replication infoDatabase mirroring
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlyesnonoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
Apache IoTDBetcdIRONdbKineticaSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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