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DBMS > Google Cloud Datastore vs. Hazelcast vs. Kyligence Enterprise vs. Microsoft Azure Synapse Analytics vs. OrigoDB

System Properties Comparison Google Cloud Datastore vs. Hazelcast vs. Kyligence Enterprise vs. Microsoft Azure Synapse Analytics vs. OrigoDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridA distributed analytics engine for big data, built on top of Apache KylinElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA fully ACID in-memory object graph database
Primary database modelDocument storeKey-value storeRelational DBMSRelational DBMSDocument store
Object oriented DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Websitecloud.google.com/­datastorehazelcast.comkyligence.io/­kyligence-enterpriseazure.microsoft.com/­services/­synapse-analyticsorigodb.com
Technical documentationcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsdocs.microsoft.com/­azure/­synapse-analyticsorigodb.com/­docs
DeveloperGoogleHazelcastKyligence, Inc.MicrosoftRobert Friberg et al
Initial release20082008201620162009 infounder the name LiveDB
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++C#
Server operating systemshostedAll OS with a Java VMLinuxhostedLinux
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesUser defined using .NET types and collections
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.noyes infothe object must implement a serialization strategynonono infocan be achieved using .NET
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageANSI SQL for queries (using Apache Calcite)yesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
.NET Client API
HTTP API
LINQ
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
PHP
.Net
Server-side scripts infoStored proceduresusing Google App Engineyes infoEvent Listeners, Executor ServicesTransact SQLyes
TriggersCallbacks using the Google Apps Engineyes infoEventsnoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioninghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoReplicated MapyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyesnono
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.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate 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-constraintsdepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlyesRole based authorization

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More resources
Google Cloud DatastoreHazelcastKyligence EnterpriseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOrigoDB
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