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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Hypertable vs. InterSystems Caché vs. Kdb

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Hypertable vs. InterSystems Caché vs. Kdb

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHypertable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonKdb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionEnterprise-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.An open source BigTable implementation based on distributed file systems such as HadoopA multi-model DBMS and application serverHigh performance Time Series DBMS
Primary database modelRelational DBMSKey-value store
Wide column store
Wide column storeKey-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
Vector DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.intersystems.com/­products/­cachekx.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.comcode.kx.com
DeveloperEsgynGoogleHypertable Inc.InterSystemsKx Systems, a division of First Derivatives plc
Initial release20152015200919972000 infokdb was released 2000, kdb+ in 2003
Current release0.9.8.11, March 20162018.1.4, May 20203.6, May 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availablecommercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++q
Server operating systemsLinuxhostedLinux
OS X
Windows infoan inofficial Windows port is available
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freedepending on used data modelyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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.nonoyesyes
Secondary indexesyesnorestricted infoonly exact value or prefix value scansyesyes infotable attribute 'grouped'
SQL infoSupport of SQLyesnonoyesSQL-like query language (q)
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
C++ API
Thrift
.NET Client API
JDBC
ODBC
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyesuser defined functions
Triggersnononoyesyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor on file system levelSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesnono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and rolesrights management via user accounts
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableHypertableInterSystems CachéKdb
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
EsgynDBGoogle Cloud BigtableHypertableInterSystems CachéKdb
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