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DBMS > Google Cloud Datastore vs. Ignite vs. MarkLogic vs. PlanetScale

System Properties Comparison Google Cloud Datastore vs. Ignite vs. MarkLogic vs. PlanetScale

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIgnite  Xexclude from comparisonMarkLogic  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionAutomatically 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.Operational and transactional Enterprise NoSQL databaseScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelDocument storeKey-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score1.59
Rank#151  Overall
#70  Relational DBMS
Websitecloud.google.com/­datastoreignite.apache.orgwww.marklogic.complanetscale.com
Technical documentationcloud.google.com/­datastore/­docsapacheignite.readme.io/­docsdocs.marklogic.complanetscale.com/­docs
DeveloperGoogleApache Software FoundationMarkLogic Corp.PlanetScale
Initial release2008201520012020
Current releaseApache Ignite 2.611.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetC++Go
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeschema-freeyesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyes, 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.noyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infoSQL92yes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScriptyes infoproprietary syntax
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
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 ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infocan act as a resource manager in an XA/JTA transactionACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsRole-based access control at the document and subdocument levelsUsers with fine-grained authorization concept infono user groups or roles

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Google Cloud DatastoreIgniteMarkLogicPlanetScale
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