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DBMS > EsgynDB vs. Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. NuoDB

System Properties Comparison EsgynDB vs. Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. NuoDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonNuoDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerNuoDB is a webscale distributed database that supports SQL and ACID transactions
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.89
Rank#198  Overall
#92  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­datastorewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.3ds.com/­nuodb-distributed-sql-database
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqldoc.nuodb.com
DeveloperEsgynGoogleKineticaMicrosoftDassault Systèmes infooriginally NuoDB, Inc.
Initial release20152008201220102013
Current release7.1, August 2021V12
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial infolimited edition free
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, C++C++C++
Server operating systemsLinuxhostedLinuxhostedhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nononoyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like DML and DDL statementsyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Proceduresusing Google App Engineuser defined functionsTransact SQLJava, SQL
TriggersnoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingdata is dynamically stored/cached on the nodes where it is read/written
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication using PaxosSource-replica replicationyes, with always 3 replicas availableyes infoManaged transparently by NuoDB
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownonono
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.Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID infotunable commit protocol
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoMVCC
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.nonoyes infoGPU vRAM or System RAMyes infoTemporary table
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 roles on table levelfine grained access rights according to SQL-standardStandard SQL roles/ privileges, Administrative Users

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More resources
EsgynDBGoogle Cloud DatastoreKineticaMicrosoft Azure SQL Database infoformerly SQL AzureNuoDB
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