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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIgnite  Xexclude from comparisonMarkLogic  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically 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 database
Primary database modelDocument store
Key-value store
Document storeKey-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
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
Websitecloud.google.com/­datastoreignite.apache.orgwww.marklogic.com
Technical documentationcloud.google.com/­datastore/­docsapacheignite.readme.io/­docsdocs.marklogic.com
DeveloperFatCloudGoogleApache Software FoundationMarkLogic Corp.
Initial release2012200820152001
Current releaseApache Ignite 2.611.0, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++, Java, .NetC++
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infoSQL92
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (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
Supported programming languagesC#.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
Server-side scripts infoStored proceduresyes infovia applicationsusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScript
Triggersyes infovia applicationsCallbacks using the Google Apps Engineyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate 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 Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 Indexes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess 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 levels

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More resources
FatDBGoogle Cloud DatastoreIgniteMarkLogic
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