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DBMS > EsgynDB vs. Google Cloud Datastore vs. Oracle NoSQL vs. Vitess

System Properties Comparison EsgynDB vs. Google Cloud Datastore vs. Oracle NoSQL vs. Vitess

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument storeDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­datastorewww.oracle.com/­database/­nosql/­technologies/­nosqlvitess.io
Technical documentationcloud.google.com/­datastore/­docsdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlvitess.io/­docs
DeveloperEsgynGoogleOracleThe Linux Foundation, PlanetScale
Initial release2015200820112013
Current release24.1, May 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaGo
Server operating systemsLinuxhostedLinux
Solaris SPARC/x86
Docker
Linux
macOS
Data schemeyesschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
Typing infopredefined data types such as float or dateyesyes, details hereoptionalyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresusing Google App Enginenoyes infoproprietary syntax
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication using PaxosElectable source-replica replication per shard. Support distributed global deployment with Multi-region table featureMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowwith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency infodepending on configuration
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsconfigurable infoACID within a storage node (=shard)ACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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 infooff heap cacheyes
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 and rolesUsers with fine-grained authorization concept infono user groups or roles

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More resources
EsgynDBGoogle Cloud DatastoreOracle NoSQLVitess
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