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DBMS > Datomic vs. Faircom EDGE vs. FatDB vs. Google Cloud Bigtable

System Properties Comparison Datomic vs. Faircom EDGE vs. FatDB vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA .NET NoSQL DBMS that can integrate with and extend SQL Server.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSKey-value store
Relational DBMS
Document store
Key-value store
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgecloud.google.com/­bigtable
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­bigtable/­docs
DeveloperCognitectFairCom CorporationFatCloudGoogle
Initial release2012197920122015
Current release1.0.6735, June 2023V3, October 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureANSI C, C++C#
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Windowshosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesno
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.noyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyes infoANSI SQL queriesno infoVia inetgration in SQL Serverno
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++yes infovia applicationsno
TriggersBy using transaction functionsyesyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGEFatDBGoogle Cloud Bigtable
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