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DBMS > Apache Phoenix vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb

System Properties Comparison Apache Phoenix vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed and scalable native Graph DBMSEnterprise-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 DBMS
Primary database modelRelational DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#131  Overall
#63  Relational DBMS
Score1.53
Rank#164  Overall
#15  Graph DBMS
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score7.69
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Websitephoenix.apache.orgdgraph.iowww.esgyn.cncloud.google.com/­bigtablekx.com
Technical documentationphoenix.apache.orgdgraph.io/­docscloud.google.com/­bigtable/­docscode.kx.com
DeveloperApache Software FoundationDgraph Labs, Inc.EsgynGoogleKx Systems, a division of First Derivatives plc
Initial release20142016201520152000 infokdb was released 2000, kdb+ in 2003
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++, Javaq
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
LinuxhostedLinux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononoyes
Secondary indexesyesyesyesnoyes infotable attribute 'grouped'
SQL infoSupport of SQLyesnoyesnoSQL-like query language (q)
APIs and other access methodsJDBCGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All 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
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Proceduresnouser defined functions
Triggersnonononoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Synchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesyesno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsno
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.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno infoPlanned for future releasesfine 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 accounts
More information provided by the system vendor
Apache PhoenixDgraphEsgynDBGoogle Cloud BigtableKdb
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
Apache PhoenixDgraphEsgynDBGoogle Cloud BigtableKdb
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