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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Graph Engine vs. Hive vs. InterSystems Caché

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

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHive  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation enginedata warehouse software for querying and managing large distributed datasets, built on HadoopA multi-model DBMS and application server
Primary database modelRelational DBMSKey-value store
Wide column store
Graph DBMS
Key-value store
Relational 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.graphengine.iohive.apache.orgwww.intersystems.com/­products/­cache
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.intersystems.com
DeveloperEsgynGoogleMicrosoftApache Software Foundation infoinitially developed by FacebookInterSystems
Initial release20152015201020121997
Current release3.1.3, April 20222018.1.4, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java.NET and CJava
Server operating systemsLinuxhosted.NETAll OS with a Java VMAIX
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
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJDBC
ODBC
Thrift
.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#
C++
F#
Visual Basic
C++
Java
PHP
Python
C#
C++
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnoyesyes infouser defined functions and integration of map-reduceyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningShardingnone
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 factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoquery execution via MapReduceno
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
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
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 rolesAccess rights for users, groups and roles

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More resources
EsgynDBGoogle Cloud BigtableGraph Engine infoformer name: TrinityHiveInterSystems Caché
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