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DBMS > Google Cloud Datastore vs. Postgres-XL vs. Sphinx vs. TerminusDB

System Properties Comparison Google Cloud Datastore vs. Postgres-XL vs. Sphinx vs. TerminusDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSphinx  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen source search engine for searching in data from different sources, e.g. relational databasesScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelDocument storeRelational DBMSSearch engineGraph DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websitecloud.google.com/­datastorewww.postgres-xl.orgsphinxsearch.comterminusdb.com
Technical documentationcloud.google.com/­datastore/­docswww.postgres-xl.org/­documentationsphinxsearch.com/­docsterminusdb.github.io/­terminusdb/­#
DeveloperGoogleSphinx Technologies Inc.DataChemist Ltd.
Initial release20082014 infosince 2012, originally named StormDB20012018
Current release10 R1, October 20183.5.1, February 202311.0.0, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licenseOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++Prolog, Rust
Server operating systemshostedLinux
macOS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesnoyes
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)yes infodistributed, parallel query executionSQL-like query language (SphinxQL)SQL-like query language (WOQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript
Python
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnoyes
TriggersCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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.Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoMVCCnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoRole-based access control

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More resources
Google Cloud DatastorePostgres-XLSphinxTerminusDB infoformer name was DataChemist
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