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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Hive vs. HugeGraph vs. InterSystems Caché

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Hive vs. HugeGraph vs. InterSystems Caché

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonInterSystems Caché  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.data warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMSA multi-model DBMS and application server
Primary database modelRelational DBMSWide column storeRelational DBMSGraph DBMSKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#281  Overall
#130  Relational DBMS
Score3.63
Rank#89  Overall
#8  Wide column stores
Score83.45
Rank#15  Overall
#10  Relational DBMS
Score0.14
Rank#300  Overall
#26  Graph DBMS
Score2.91
Rank#102  Overall
#18  Key-value stores
#1  Object oriented DBMS
#53  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablehive.apache.orggithub.com/­hugegraphwww.intersystems.com/­products/­cache
Technical documentationcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.github.io/­hugegraph-docdocs.intersystems.com
DeveloperEsgynGoogleApache Software Foundation infoinitially developed by FacebookBaiduInterSystems
Initial release20152015201220181997
Current release3.1.2, August 20190.92018.1.4, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
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++, JavaJavaJava
Server operating systemsLinuxhostedAll OS with a Java VMLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesdepending on used data model
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.nononoyes
Secondary indexesyesnoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Groovy
Java
Python
C#
C++
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
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 zonesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoquery execution via MapReducevia hugegraph-sparkno
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 ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDACID
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
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)Access rights for users, groups and rolesUsers, roles and permissionsAccess rights for users, groups and roles

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More resources
EsgynDBGoogle Cloud BigtableHiveHugeGraphInterSystems Caché
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