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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Synapse Analytics vs. STSdb vs. TerminusDB

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Synapse Analytics vs. STSdb vs. TerminusDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSTSdb  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelDocument storeTime Series DBMSRelational DBMSKey-value storeGraph DBMS
Secondary database modelsDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websitecloud.google.com/­datastorewww.hawkular.orgazure.microsoft.com/­services/­synapse-analyticsgithub.com/­STSSoft/­STSdb4terminusdb.com
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­azure/­synapse-analyticsterminusdb.github.io/­terminusdb/­#
DeveloperGoogleCommunity supported by Red HatMicrosoftSTS Soft SCDataChemist Ltd.
Initial release20082014201620112018
Current release4.0.8, September 201511.0.0, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPLv2, commercial license availableOpen Source infoGPL V3
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#Prolog, Rust
Server operating systemshostedLinux
OS X
Windows
hostedWindowsLinux
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes infoprimitive types and user defined types (classes)yes
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 indexesyesnoyesno
SQL infoSupport of SQLSQL-like query language (GQL)noyesnoSQL-like query language (WOQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTADO.NET
JDBC
ODBC
.NET Client APIOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C#
Java
PHP
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresusing Google App EnginenoTransact SQLnoyes
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding, horizontal partitioningnoneGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandrayesnoneJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate 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-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyesnoRole-based access control

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More resources
Google Cloud DatastoreHawkular MetricsMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSTSdbTerminusDB infoformer name was DataChemist
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