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DBMS > FatDB vs. Google Cloud Datastore vs. Immudb vs. Ingres vs. Trafodion

System Properties Comparison FatDB vs. Google Cloud Datastore vs. Immudb vs. Ingres vs. Trafodion

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonImmudb  Xexclude from comparisonIngres  Xexclude from comparisonTrafodion  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines 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 PlatformAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Well established RDBMSTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Key-value store
Document storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.24
Rank#305  Overall
#43  Key-value stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­codenotary/­immudb
immudb.io
www.actian.com/­databases/­ingrestrafodion.apache.org
Technical documentationcloud.google.com/­datastore/­docsdocs.immudb.iodocs.actian.com/­ingrestrafodion.apache.org/­documentation.html
DeveloperFatCloudGoogleCodenotaryActian CorporationApache Software Foundation, originally developed by HP
Initial release2012200820201974 infooriginally developed at University Berkely in early 1970s2014
Current release1.2.3, April 202211.2, May 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
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 languageC#GoCC++, Java
Server operating systemsWindowshostedBSD
Linux
macOS
Solaris
Windows
z/OS
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
Data schemeschema-freeschema-freeschema-freeyesyes
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.nonono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)SQL-like syntaxyesyes
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
gRPC protocol
PostgreSQL wire protocol
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infovia applicationsusing Google App EnginenoyesJava Stored Procedures
Triggersyes infovia applicationsCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosIngres Replicatoryes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownonoyes infovia user defined functions and HBase
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
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)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
FatDBGoogle Cloud DatastoreImmudbIngresTrafodion
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