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DBMS > Datomic vs. EsgynDB vs. Faircom EDGE vs. Firebase Realtime Database vs. Google Cloud Bigtable

System Properties Comparison Datomic vs. EsgynDB vs. Faircom EDGE vs. Firebase Realtime Database vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.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 DBMSRelational DBMSKey-value store
Relational DBMS
Document storeKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score0.02
Rank#370  Overall
#55  Key-value stores
#157  Relational DBMS
Score13.60
Rank#39  Overall
#6  Document stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Websitewww.datomic.comwww.esgyn.cnwww.faircom.com/­products/­faircom-edgefirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtable
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docs
DeveloperCognitectEsgynFairCom CorporationGoogle infoacquired by Google 2014Google
Initial release20122015197920122015
Current release1.0.7180, July 2024V3, October 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++, JavaANSI C, C++
Server operating systemsAll OS with a Java VMLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
hostedhosted
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, 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.nonoyesnono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnoyesyes infoANSI SQL queriesnono
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Java
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava Stored Proceduresyes info.Net, JavaScript, C/C++limited functionality with using 'rules'no
TriggersBy using transaction functionsnoyesCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication between multi datacentersyes infoSynchronous and asynchronous realtime replication based on transaction logsInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDyesAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentnoyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatomicEsgynDBFaircom EDGE infoformerly c-treeEDGEFirebase Realtime DatabaseGoogle Cloud Bigtable
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