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DBMS > Apache IoTDB vs. etcd vs. GeoSpock vs. IRONdb vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. etcd vs. GeoSpock vs. IRONdb vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonetcd  Xexclude from comparisonGeoSpock  Xexclude from comparisonIRONdb  Xexclude from comparisonPostgres-XL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.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 storeSpatial and temporal data processing engine for extreme data scaleA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelTime Series DBMSKey-value storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteiotdb.apache.orgetcd.io
github.com/­etcd-io/­etcd
geospock.comwww.circonus.com/solutions/time-series-database/www.postgres-xl.org
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-startedwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationGeoSpockCirconus LLC.
Initial release201820172014 infosince 2012, originally named StormDB
Current release1.1.0, April 20233.4, August 20192.0, September 2019V0.10.20, January 201810 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialcommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava, JavascriptC and C++C
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
Windows infoexperimental
hostedLinuxLinux
macOS
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes infotext, numeric, histogramsyes
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 infoXML type, but no XML query functionality
Secondary indexesyesnotemporal, categoricalnoyes
SQL infoSupport of SQLSQL-like query languagenoANSI SQL for query only (using Presto)SQL-like query language (Circonus Analytics Query Language: CAQL)yes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
gRPC
JSON over HTTP
JDBCHTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesnonoyes, in Luauser defined functions
Triggersyesyes, watching key changesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic shardingAutomatic, metric affinity per nodehorizontal partitioning
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 aware
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 ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID infoMVCC
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.yesnononono
User concepts infoAccess controlyesnoAccess rights for users can be defined per tablenofine grained access rights according to SQL-standard

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More resources
Apache IoTDBetcdGeoSpockIRONdbPostgres-XL
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