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

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

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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 TrafodionCloud-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.An open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Wide column 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
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitewww.datomic.comwww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtable
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docs
DeveloperCognitectEsgynGoogle infoacquired by Google 2014GoogleHypertable Inc.
Initial release20122015201220152009
Current release1.0.7075, December 20230.9.8.11, March 2016
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++, JavaC++
Server operating systemsAll OS with a Java VMLinuxhostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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.nononono
Secondary indexesyesyesyesnorestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLnoyesnonono
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
C++ API
Thrift
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava Stored Procedureslimited functionality with using 'rules'nono
TriggersBy using transaction functionsnoCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual 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)Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 developmentnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
DatomicEsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableHypertable
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