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DBMS > EsgynDB vs. HBase vs. IBM Db2 Event Store vs. Kdb

System Properties Comparison EsgynDB vs. HBase vs. IBM Db2 Event Store vs. Kdb

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHBase  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWide-column store based on Apache Hadoop and on concepts of BigTableDistributed Event Store optimized for Internet of Things use casesHigh performance Time Series DBMS
Primary database modelRelational DBMSWide column storeEvent Store
Time Series DBMS
Time Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websitewww.esgyn.cnhbase.apache.orgwww.ibm.com/­products/­db2-event-storekx.com
Technical documentationhbase.apache.org/­book.htmlwww.ibm.com/­docs/­en/­db2-event-storecode.kx.com
DeveloperEsgynApache Software Foundation infoApache top-level project, originally developed by PowersetIBMKx Systems, a division of First Derivatives plc
Initial release2015200820172000 infokdb was released 2000, kdb+ in 2003
Current release2.3.4, January 20212.03.6, May 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercial infofree developer edition availablecommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaC and C++q
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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.nononoyes
Secondary indexesyesnonoyes infotable attribute 'grouped'
SQL infoSupport of SQLyesnoyes infothrough the embedded Spark runtimeSQL-like query language (q)
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresyes infoCoprocessors in Javayesuser defined functions
Triggersnoyesnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication
Source-replica replication
Active-active shard replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardrights management via user accounts
More information provided by the system vendor
EsgynDBHBaseIBM Db2 Event StoreKdb
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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EsgynDBHBaseIBM Db2 Event StoreKdb
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