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DBMS > EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. Kinetica vs. SiteWhere

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. Kinetica vs. SiteWhere

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparisonSiteWhere  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 DBMSFully vectorized database across both GPUs and CPUsM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSKey-value store
Wide column store
Graph DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.comgithub.com/­sitewhere/­sitewhere
Technical documentationcloud.google.com/­bigtable/­docshugegraph.apache.org/­docsdocs.kinetica.comsitewhere1.sitewhere.io/­index.html
DeveloperEsgynGoogleBaiduKineticaSiteWhere
Initial release20152015201820122010
Current release0.97.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialOpen Source infoCommon Public Attribution License Version 1.0
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++, JavaJavaC, C++Java
Server operating systemsLinuxhostedLinux
macOS
Unix
LinuxLinux
OS X
Windows
Data schemeyesschema-freeyesyespredefined scheme
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.nonononono
Secondary indexesyesnoyes infoalso supports composite index and range indexyesno
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statementsno
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
JDBC
ODBC
RESTful HTTP API
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnoasynchronous Gremlin script jobsuser defined functions
Triggersnononoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infobased on HBase
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 replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesvia hugegraph-sparknono
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 Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoedges in graphyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDnono
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.nonoyesyes infoGPU vRAM or System RAMno
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 permissionsAccess rights for users and roles on table levelUsers with fine-grained authorization concept

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More resources
EsgynDBGoogle Cloud BigtableHugeGraphKineticaSiteWhere
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