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DBMS > EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. Sqrrl

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. InterSystems Caché vs. Sqrrl

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSqrrl  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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 serverAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Document store
Graph DBMS
Key-value store
Wide column store
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
Websitewww.esgyn.cncloud.google.com/­bigtablewww.intersystems.com/­products/­cachesqrrl.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.com
DeveloperEsgynGoogleInterSystemsAmazon infooriginally Sqrrl Data, Inc.
Initial release2015201519972012
Current release2018.1.4, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freedepending on used data modelschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoyesno
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
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresJava Stored Proceduresnoyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infomaking use of Hadoop
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 replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyes
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 Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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 rolesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
EsgynDBGoogle Cloud BigtableInterSystems CachéSqrrl
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