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DBMS > Google BigQuery vs. Hawkular Metrics vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage vs. Netezza

System Properties Comparison Google BigQuery vs. Hawkular Metrics vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage vs. Netezza

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesHawkular 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 ServerA Wide Column Store for rapid development using massive semi-structured datasetsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSTime Series DBMSRelational DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitecloud.google.com/­bigquerywww.hawkular.orgazure.microsoft.com/­services/­synapse-analyticsazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezza
Technical documentationcloud.google.com/­bigquery/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­azure/­synapse-analytics
DeveloperGoogleCommunity supported by Red HatMicrosoftMicrosoftIBM
Initial release20102014201620122000
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Windows
hostedhostedLinux infoincluded in appliance
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesnonoyesnoyes
SQL infoSupport of SQLyesnoyesnoyes
APIs and other access methodsRESTful HTTP/JSON APIHTTP RESTADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
OLE DB
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Go
Java
Python
Ruby
C#
Java
PHP
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnoTransact SQLnoyes
Triggersnoyes infovia Hawkular Alertingnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding, horizontal partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoACIDoptimistic lockingACID
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.nonono
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)noyesAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization concept

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More resources
Google BigQueryHawkular MetricsMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMicrosoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBM
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