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DBMS > FeatureBase vs. Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure SQL Database vs. STSdb

System Properties Comparison FeatureBase vs. Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure SQL Database vs. STSdb

Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Automatically 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.Database as a Service offering with high compatibility to Microsoft SQL ServerKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.featurebase.comcloud.google.com/­datastorewww.hawkular.orgazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­STSSoft/­STSdb4
Technical documentationdocs.featurebase.comcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperMolecula and Pilosa Open Source ContributorsGoogleCommunity supported by Red HatMicrosoftSTS Soft SC
Initial release20172008201420102011
Current release2022, May 2022V124.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoGPLv2, commercial license available
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 languageGoJavaC++C#
Server operating systemsLinux
macOS
hostedLinux
OS X
Windows
hostedWindows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes infoprimitive types and user defined types (classes)
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.nononoyes
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLSQL queriesSQL-like query language (GQL)noyesno
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTADO.NET
JDBC
ODBC
.NET Client API
Supported programming languagesJava
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
Server-side scripts infoStored proceduresusing Google App EnginenoTransact SQLno
TriggersnoCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardno

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More resources
FeatureBaseGoogle Cloud DatastoreHawkular MetricsMicrosoft Azure SQL Database infoformerly SQL AzureSTSdb
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