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DBMS > Datomic vs. EXASOL vs. Fujitsu Enterprise Postgres vs. Google Cloud Spanner vs. NSDb

System Properties Comparison Datomic vs. EXASOL vs. Fujitsu Enterprise Postgres vs. Google Cloud Spanner vs. NSDb

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEXASOL  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websitewww.datomic.comwww.exasol.comwww.postgresql.fastware.comcloud.google.com/­spannernsdb.io
Technical documentationdocs.datomic.comwww.exasol.com/­resourceswww.postgresql.fastware.com/­product-manualscloud.google.com/­spanner/­docsnsdb.io/­Architecture
DeveloperCognitectExasolPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogle
Initial release2012200020172017
Current release1.0.6735, June 2023Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureCJava, Scala
Server operating systemsAll OS with a Java VMLinux
Windows
hostedLinux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes: int, bigint, decimal, string
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
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyesyesyes infoQuery statements complying to ANSI 2011SQL-like query language
APIs and other access methodsRESTful HTTP API.Net
JDBC
ODBC
WebSocket
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languagesClojure
Java
Java
Lua
Python
R
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
Java
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsuser defined functionsnono
TriggersBy using transaction functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingpartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesUsing Apache Lucene
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 developmentyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
DatomicEXASOLFujitsu Enterprise PostgresGoogle Cloud SpannerNSDb
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
DatomicEXASOLFujitsu Enterprise PostgresGoogle Cloud SpannerNSDb
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