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DBMS > Google Cloud Datastore vs. Percona Server for MySQL vs. Solr vs. TerminusDB

System Properties Comparison Google Cloud Datastore vs. Percona Server for MySQL vs. Solr vs. TerminusDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPercona Server for MySQL  Xexclude from comparisonSolr  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEnhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.A widely used distributed, scalable search engine based on Apache LuceneScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelDocument storeRelational DBMSSearch engineGraph DBMS
Secondary database modelsSpatial DBMSDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score2.10
Rank#119  Overall
#57  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.23
Rank#316  Overall
#27  Graph DBMS
Websitecloud.google.com/­datastorewww.percona.com/­software/­mysql-database/­percona-serversolr.apache.orgterminusdb.com
Technical documentationcloud.google.com/­datastore/­docswww.percona.com/­downloads/­Percona-Server-LATESTsolr.apache.org/­resources.htmlterminusdb.github.io/­terminusdb/­#
DeveloperGooglePerconaApache Software FoundationDataChemist Ltd.
Initial release2008200820062018
Current release8.0.36-28, 20249.6.1, May 202411.0.0, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2Open Source infoApache Version 2Open 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 languageC and C++JavaProlog, Rust
Server operating systemshostedLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infosupports customizable data types and automatic typingyes
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.noyesyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)yesSolr Parallel SQL InterfaceSQL-like query language (WOQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript
Python
Server-side scripts infoStored proceduresusing Google App EngineyesJava pluginsyes
TriggersCallbacks using the Google Apps Engineyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
XtraDB Cluster
yesJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
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 ConsistencyEventual 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 TransactionsACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or rolesyesRole-based access control

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More resources
Google Cloud DatastorePercona Server for MySQLSolrTerminusDB infoformer name was DataChemist
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