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DBMS > EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. Microsoft Azure SQL Database vs. PouchDB

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. Microsoft Azure SQL Database vs. PouchDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPouchDB  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 multi-model DBMS and application serverDatabase as a Service offering with high compatibility to Microsoft SQL ServerJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSDocument store
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial 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
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websitewww.esgyn.cncloud.google.com/­bigtablewww.intersystems.com/­products/­cacheazure.microsoft.com/­en-us/­products/­azure-sql/­databasepouchdb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­azure-sqlpouchdb.com/­guides
DeveloperEsgynGoogleInterSystemsMicrosoftApache Software Foundation
Initial release20152015199720102012
Current release2018.1.4, May 2020V127.1.1, June 2019
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++JavaScript
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freedepending on used data modelyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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.nonoyesyesno
Secondary indexesyesnoyesyesyes infovia views
SQL infoSupport of SQLyesnoyesyesno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresJava Stored ProceduresnoyesTransact SQLView functions in JavaScript
Triggersnonoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infowith a proxy-based framework, named couchdb-lounge
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 zonesSource-replica replicationyes, with always 3 replicas availableMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
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 rolesfine grained access rights according to SQL-standardno

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More resources
EsgynDBGoogle Cloud BigtableInterSystems CachéMicrosoft Azure SQL Database infoformerly SQL AzurePouchDB
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