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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. Riak KV

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. Riak KV

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonRiak KV  Xexclude from comparison
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.High performance Time Series DBMSDistributed, fault tolerant key-value store
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score4.44
Rank#80  Overall
#9  Key-value stores
Websitewww.esgyn.cncloud.google.com/­bigtablekx.com
Technical documentationcloud.google.com/­bigtable/­docscode.kx.comwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperEsgynGoogleKx Systems, a division of First Derivatives plcOpenSource, formerly Basho Technologies
Initial release201520152000 infokdb was released 2000, kdb+ in 20032009
Current release3.6, May 20183.2.0, December 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree 32-bit versionOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaqErlang
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Linux
OS X
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.nonoyesno
Secondary indexesyesnoyes infotable attribute 'grouped'restricted
SQL infoSupport of SQLyesnoSQL-like query language (q)no
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
HTTP API
Native Erlang Interface
Supported programming languagesAll 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
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresnouser defined functionsErlang
Triggersnonoyes infowith viewsyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding infono "single point of failure"
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 zonesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infosimilar paradigm used for internal processingyes
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 ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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)rights management via user accountsyes, using Riak Security
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableKdbRiak KV
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 BigtableKdbRiak KV
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