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DBMS > Dolt vs. Google Cloud Datastore vs. Oracle Coherence vs. Spark SQL vs. Transbase

System Properties Comparison Dolt vs. Google Cloud Datastore vs. Oracle Coherence vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameDolt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle Coherence  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA MySQL compatible DBMS with Git-like versioning of data and schemaAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOracles in-memory data grid solutionSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.97
Rank#129  Overall
#22  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitegithub.com/­dolthub/­dolt
www.dolthub.com
cloud.google.com/­datastorewww.oracle.com/­java/­coherencespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.dolthub.comcloud.google.com/­datastore/­docsdocs.oracle.com/­en/­middleware/­standalone/­coherencespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperDoltHub IncGoogleOracleApache Software FoundationTransaction Software GmbH
Initial release20182008200720141987
Current release14.1, August 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaScalaC and C++
Server operating systemsLinux
macOS
Windows
hostedAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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 indexesyesyesnonoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noSQL-like DML and DDL statementsyes
APIs and other access methodsCLI Client
HTTP REST
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infocurrently in alpha releaseusing Google App Enginenonoyes
TriggersyesCallbacks using the Google Apps Engineyes infoLive Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Multi-source replication using Paxosyes, with selectable consistency levelnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsconfigurablenoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptionallyyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)authentification to access the cache via certificates or http basic authenticationnofine grained access rights according to SQL-standard

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More resources
DoltGoogle Cloud DatastoreOracle CoherenceSpark SQLTransbase
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