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DBMS > Datomic vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb

System Properties Comparison Datomic vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.High performance Time Series DBMS
Primary database modelRelational DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score1.48
Rank#158  Overall
#15  Graph DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score7.70
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitewww.datomic.comdgraph.iowww.esgyn.cncloud.google.com/­bigtablekx.com
Technical documentationdocs.datomic.comdgraph.io/­docscloud.google.com/­bigtable/­docscode.kx.com
DeveloperCognitectDgraph Labs, Inc.EsgynGoogleKx Systems, a division of First Derivatives plc
Initial release20122016201520152000 infokdb was released 2000, kdb+ in 2003
Current release1.0.6735, June 20233.6, May 2018
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercialcommercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureGoC++, Javaq
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononoyes
Secondary indexesyesyesyesnoyes infotable attribute 'grouped'
SQL infoSupport of SQLnonoyesnoSQL-like query language (q)
APIs and other access methodsRESTful HTTP APIGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoJava Stored Proceduresnouser defined functions
TriggersBy using transaction functionsnononoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic 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 developmentnonoyes
User concepts infoAccess controlnono infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accounts
More information provided by the system vendor
DatomicDgraphEsgynDBGoogle Cloud BigtableKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
DatomicDgraphEsgynDBGoogle Cloud BigtableKdb
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