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DBMS > Datomic vs. etcd vs. IRONdb vs. RocksDB vs. TimesTen

System Properties Comparison Datomic vs. etcd vs. IRONdb vs. RocksDB vs. TimesTen

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonetcd  Xexclude from comparisonIRONdb  Xexclude from comparisonRocksDB  Xexclude from comparisonTimesTen  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed reliable key-value storeA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityEmbeddable persistent key-value store optimized for fast storage (flash and RAM)An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelRelational DBMSKey-value storeTime Series DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score7.05
Rank#53  Overall
#5  Key-value stores
Score2.84
Rank#97  Overall
#16  Key-value stores
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitewww.datomic.cometcd.io
github.com/­etcd-io/­etcd
www.circonus.com/solutions/time-series-database/rocksdb.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.circonus.com/irondb/category/getting-startedgithub.com/­facebook/­rocksdb/­wikidocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperCognitectCirconus LLC.Facebook, Inc.Oracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012201720131998
Current release1.0.7180, July 20243.4, August 2019V0.10.20, January 20189.4.0, June 2024Release 22.1
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0commercialOpen Source infoBSDcommercial
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 languageJava, ClojureGoC and C++C++
Server operating systemsAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
LinuxLinuxIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes infotext, numeric, histogramsnoyes
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.nonononono
Secondary indexesyesnononoyes
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methodsRESTful HTTP APIgRPC
JSON over HTTP
HTTP APIC++ API
Java API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesClojure
Java
.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
C++
Go
Java
Perl
Python
Ruby
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes, in LuanoPL/SQL
TriggersBy using transaction functionsyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersAutomatic, metric affinity per nodehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.configurable replication factor, datacenter awareyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnonoyesyes
User concepts infoAccess controlnonononofine grained access rights according to SQL-standard

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More resources
DatomicetcdIRONdbRocksDBTimesTen
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