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DBMS > EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. Linter vs. Microsoft Azure Table Storage

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. Linter vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Table Storage  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 serverRDBMS for high security requirementsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSWide column store
Secondary database modelsDocument storeSpatial 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
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitewww.esgyn.cncloud.google.com/­bigtablewww.intersystems.com/­products/­cachelinter.ruazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.com
DeveloperEsgynGoogleInterSystemsrelex.ruMicrosoft
Initial release20152015199719902012
Current release2018.1.4, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC and C++
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeyesschema-freedepending on used data modelyesschema-free
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.nonoyesnono
Secondary indexesyesnoyesyesno
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
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Proceduresnoyesyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneSharding infoImplicit feature of the cloud service
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 replicationSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACIDoptimistic locking
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.nonoyesno
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-standardAccess rights based on private key authentication or shared access signatures

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More resources
EsgynDBGoogle Cloud BigtableInterSystems CachéLinterMicrosoft Azure Table Storage
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