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DBMS > Google Cloud Datastore vs. Hive vs. Microsoft Azure Synapse Analytics vs. Trafodion vs. VelocityDB

System Properties Comparison Google Cloud Datastore vs. Hive vs. Microsoft Azure Synapse Analytics vs. Trafodion vs. VelocityDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTrafodion  Xexclude from comparisonVelocityDB  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerTransactional SQL-on-Hadoop DBMSA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitecloud.google.com/­datastorehive.apache.orgazure.microsoft.com/­services/­synapse-analyticstrafodion.apache.orgvelocitydb.com
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­azure/­synapse-analyticstrafodion.apache.org/­documentation.htmlvelocitydb.com/­UserGuide
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookMicrosoftApache Software Foundation, originally developed by HPVelocityDB Inc
Initial release20082012201620142011
Current release3.1.3, April 20222.3.0, February 20197.x
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, JavaC#
Server operating systemshostedAll OS with a Java VMhostedLinuxAny that supports .NET
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.nononono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
.Net
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C#
Java
PHP
All languages supporting JDBC/ODBC/ADO.Net.Net
Server-side scripts infoStored proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceTransact SQLJava Stored Proceduresno
TriggersCallbacks using the Google Apps EnginenononoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factoryesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReducenoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACIDACID
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesyesfine grained access rights according to SQL-standardBased on Windows Authentication

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More resources
Google Cloud DatastoreHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTrafodionVelocityDB
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