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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. VoltDB

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. VoltDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonVoltDB  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 In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Relational DBMS
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
Score1.46
Rank#159  Overall
#74  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablekx.comwww.voltdb.com
Technical documentationcloud.google.com/­bigtable/­docscode.kx.comdocs.voltdb.com
DeveloperEsgynGoogleKx Systems, a division of First Derivatives plcVoltDB Inc.
Initial release201520152000 infokdb was released 2000, kdb+ in 20032010
Current release3.6, May 201811.3, April 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree 32-bit versionOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaqJava, C++
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Linux
OS X infofor development
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes
Secondary indexesyesnoyes infotable attribute 'grouped'yes
SQL infoSupport of SQLyesnoSQL-like query language (q)yes infoonly a subset of SQL 99
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
Java API
JDBC
RESTful HTTP/JSON API
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#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnouser defined functionsJava
Triggersnonoyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
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 replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infosimilar paradigm used for internal processingno
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 Consistency
Foreign keys infoReferential integrityyesnoyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
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 accountsUsers and roles with access to stored procedures
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableKdbVoltDB
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 BigtableKdbVoltDB
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