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DBMS > Datomic vs. Google Cloud Datastore vs. Ignite vs. PostgreSQL

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Ignite vs. PostgreSQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIgnite  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitewww.datomic.comcloud.google.com/­datastoreignite.apache.orgwww.postgresql.org
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsapacheignite.readme.io/­docswww.postgresql.org/­docs
DeveloperCognitectGoogleApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2012200820151989 info1989: Postgres, 1996: PostgreSQL
Current release1.0.7075, December 2023Apache Ignite 2.616.3, May 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++, Java, .NetC
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonoyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infostandard with numerous extensions
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineyes (compute grid and cache interceptors can be used instead)user defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosyes (replicated cache)Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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
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 developmentnoyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
DatomicGoogle Cloud DatastoreIgnitePostgreSQL
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