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DBMS > EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. Kdb vs. TinkerGraph

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. Kdb vs. TinkerGraph

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonKdb  Xexclude from comparisonTinkerGraph  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.A fast-speed and highly-scalable Graph DBMSHigh performance Time Series DBMSA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelRelational DBMSKey-value store
Wide column store
Graph DBMSTime Series DBMS
Vector DBMS
Graph DBMS
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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
kx.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcloud.google.com/­bigtable/­docshugegraph.apache.org/­docscode.kx.com
DeveloperEsgynGoogleBaiduKx Systems, a division of First Derivatives plc
Initial release2015201520182000 infokdb was released 2000, kdb+ in 20032009
Current release0.93.6, May 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial infofree 32-bit versionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaqJava
Server operating systemsLinuxhostedLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononoyesno
Secondary indexesyesnoyes infoalso supports composite index and range indexyes infotable attribute 'grouped'no
SQL infoSupport of SQLyesnonoSQL-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)
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Groovy
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnoasynchronous Gremlin script jobsuser defined functionsno
Triggersnononoyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioningnone
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 zonesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesvia hugegraph-sparkno 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)Eventual ConsistencyImmediate Consistencynone
Foreign keys infoReferential integrityyesnoyes infoedges in graphyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
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)Users, roles and permissionsrights management via user accountsno
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableHugeGraphKdbTinkerGraph
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 BigtableHugeGraphKdbTinkerGraph
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