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DBMS > EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. PouchDB vs. Prometheus

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. PouchDB vs. Prometheus

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonPouchDB  Xexclude from comparisonPrometheus  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 serverJavaScript DBMS with an API inspired by CouchDBOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Document storeTime Series 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
Score2.28
Rank#115  Overall
#21  Document stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.intersystems.com/­products/­cachepouchdb.comprometheus.io
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.compouchdb.com/­guidesprometheus.io/­docs
DeveloperEsgynGoogleInterSystemsApache Software Foundation
Initial release20152015199720122015
Current release2018.1.4, May 20207.1.1, June 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen SourceOpen Source infoApache 2.0
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++, JavaJavaScriptGo
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
Windows
Data schemeyesschema-freedepending on used data modelschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoNumeric data only
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.nonoyesnono infoImport of XML data possible
Secondary indexesyesnoyesyes infovia viewsno
SQL infoSupport of SQLyesnoyesnono
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
HTTP REST infoonly for PouchDB Server
JavaScript API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresJava Stored ProceduresnoyesView functions in JavaScriptno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infowith a proxy-based framework, named couchdb-loungeSharding
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 replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyesno
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 ConsistencyEventual Consistencynone
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesno
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 rolesnono

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More resources
EsgynDBGoogle Cloud BigtableInterSystems CachéPouchDBPrometheus
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