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DBMS > Datomic vs. Hawkular Metrics vs. Hypertable vs. Tarantool

System Properties Comparison Datomic vs. Hawkular Metrics vs. Hypertable vs. Tarantool

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHypertable  Xexclude from comparisonTarantool  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An open source BigTable implementation based on distributed file systems such as HadoopIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSTime Series DBMSWide column storeKey-value store
Secondary database modelsDocument store
Relational DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#133  Overall
#66  Relational DBMS
Score0.16
Rank#328  Overall
#29  Time Series DBMS
Score1.77
Rank#143  Overall
#27  Key-value stores
Websitewww.datomic.comwww.hawkular.orgwww.tarantool.io
Technical documentationdocs.datomic.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.tarantool.io/­en/­doc
DeveloperCognitectCommunity supported by Red HatHypertable Inc.VK
Initial release2012201420092008
Current release1.0.6362, January 20220.9.8.11, March 20162.10.0, May 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJavaC++C and C++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
BSD
Linux
macOS
Data schemeyesschema-freeschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesnostring, double, decimal, uuid, integer, blob, boolean
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.nonono
Secondary indexesyesnorestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnononoFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIHTTP RESTC++ API
Thrift
Open binary protocol
Supported programming languagesClojure
Java
Go
Java
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnonoLua, C and SQL stored procedures
TriggersBy using transaction functionsyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infobased on CassandraShardingHash sharding based on virtual buckets
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factor infobased on Cassandraselectable replication factor on file system levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes, with SQL
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID, read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes, regular snapshots on disk, write ahead logging
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 developmentnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnononoAccess rights for users and roles

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More resources
DatomicHawkular MetricsHypertableTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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