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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. LeanXcale vs. PouchDB

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. LeanXcale vs. PouchDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonLeanXcale  Xexclude from comparisonPouchDB  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 DBMSA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Key-value store
Relational DBMS
Document store
Secondary database modelsRelational 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
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websitewww.esgyn.cncloud.google.com/­bigtablekx.comwww.leanxcale.compouchdb.com
Technical documentationcloud.google.com/­bigtable/­docscode.kx.compouchdb.com/­guides
DeveloperEsgynGoogleKx Systems, a division of First Derivatives plcLeanXcaleApache Software Foundation
Initial release201520152000 infokdb was released 2000, kdb+ in 200320152012
Current release3.6, May 20187.1.1, June 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree 32-bit versioncommercialOpen Source
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++, JavaqJavaScript
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeyesyesschema-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'yes infovia views
SQL infoSupport of SQLyesnoSQL-like query language (q)yes infothrough Apache Derbyno
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
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
HTTP REST infoonly for PouchDB Server
JavaScript 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
Java
Scala
JavaScript
Server-side scripts infoStored proceduresJava Stored Proceduresnouser defined functionsView functions in JavaScript
Triggersnonoyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding infowith a proxy-based framework, named couchdb-lounge
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 infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infosimilar paradigm used for internal processingnoyes
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 ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
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 accountsno
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableKdbLeanXcalePouchDB
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 BigtableKdbLeanXcalePouchDB
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