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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonPouchDB  Xexclude from comparison
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 environmentsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.JavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value store
Wide column store
Document 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
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgecloud.google.com/­bigtablepouchdb.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­bigtable/­docspouchdb.com/­guides
DeveloperCognitectFairCom CorporationGoogleApache Software Foundation
Initial release2012197920152012
Current release1.0.7075, December 2023V3, October 20207.1.1, June 2019
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureANSI C, C++JavaScript
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesnono
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.noyesnono
Secondary indexesyesyesnoyes infovia views
SQL infoSupport of SQLnoyes infoANSI SQL queriesnono
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++noView functions in JavaScript
TriggersBy using transaction functionsyesnoyes
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 infowith a proxy-based framework, named couchdb-lounge
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 logsInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
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 developmentyesnoyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGEGoogle Cloud BigtablePouchDB
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