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DBMS > FeatureBase vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Netezza

System Properties Comparison FeatureBase vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Netezza

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitewww.featurebase.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­synapse-analyticswww.ibm.com/­products/­netezza
Technical documentationdocs.featurebase.comspotify.github.io/­heroicdocs.microsoft.com/­azure/­synapse-analytics
DeveloperMolecula and Pilosa Open Source ContributorsSpotifyMicrosoftIBM
Initial release2017201420162000
Current release2022, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++
Server operating systemsLinux
macOS
hostedLinux infoincluded in appliance
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLSQL queriesnoyesyes
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
Supported programming languagesJava
Python
C#
Java
PHP
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoTransact SQLyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesUsers with fine-grained authorization concept

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More resources
FeatureBaseHeroicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNetezza infoAlso called PureData System for Analytics by IBM
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