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DBMS > Datomic vs. EsgynDB vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. Kdb

System Properties Comparison Datomic vs. EsgynDB vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. Kdb

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonKdb  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 TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Cloud-based data warehousing serviceHigh performance Time Series DBMS
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMSTime Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitewww.datomic.comwww.esgyn.cncloud.google.com/­bigtablewww.ibm.com/­products/­db2/­warehousekx.com
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docscode.kx.com
DeveloperCognitectEsgynGoogleIBMKx Systems, a division of First Derivatives plc
Initial release20122015201520142000 infokdb was released 2000, kdb+ in 2003
Current release1.0.6735, June 20233.6, May 2018
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++, Javaq
Server operating systemsAll OS with a Java VMLinuxhostedhostedLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 infoImport/export of XML data possibleyes
Secondary indexesyesyesnoyesyes infotable attribute 'grouped'
SQL infoSupport of SQLnoyesnoyesSQL-like query language (q)
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
OLE DB
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesClojure
Java
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava Stored ProceduresnoPL/SQL, SQL PLuser defined functions
TriggersBy using transaction functionsnonoyesyes infowith views
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingShardinghorizontal partitioning
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 zonesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACIDno
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 developmentnonoyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardrights management via user accounts
More information provided by the system vendor
DatomicEsgynDBGoogle Cloud BigtableIBM Db2 warehouse infoformerly named IBM dashDBKdb
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
DatomicEsgynDBGoogle Cloud BigtableIBM Db2 warehouse infoformerly named IBM dashDBKdb
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