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DBMS > Datomic vs. Google Cloud Bigtable vs. HBase vs. OrigoDB

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. HBase vs. OrigoDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableA fully ACID in-memory object graph database
Primary database modelRelational DBMSKey-value store
Wide column store
Wide column storeDocument store
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websitewww.datomic.comcloud.google.com/­bigtablehbase.apache.orgorigodb.com
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlorigodb.com/­docs
DeveloperCognitectGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetRobert Friberg et al
Initial release2012201520082009 infounder the name LiveDB
Current release1.0.6735, June 20232.3.4, January 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache version 2Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC#
Server operating systemsAll OS with a Java VMhostedLinux
Unix
Windows infousing Cygwin
Linux
Windows
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROUser defined using .NET types and collections
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.nononono infocan be achieved using .NET
Secondary indexesyesnonoyes
SQL infoSupport of SQLnononono
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
.NET Client API
HTTP API
LINQ
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infoCoprocessors in Javayes
TriggersBy using transaction functionsnoyesyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoWrite ahead log
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 developmentnoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole based authorization

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More resources
DatomicGoogle Cloud BigtableHBaseOrigoDB
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