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DBMS > Microsoft Azure Synapse Analytics vs. NSDb vs. Spark SQL vs. WakandaDB

System Properties Comparison Microsoft Azure Synapse Analytics vs. NSDb vs. Spark SQL vs. WakandaDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSTime Series DBMSRelational DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteazure.microsoft.com/­services/­synapse-analyticsnsdb.iospark.apache.org/­sqlwakanda.github.io
Technical documentationdocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperMicrosoftApache Software FoundationWakanda SAS
Initial release2016201720142012
Current release3.5.0 ( 2.13), September 20232.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, ScalaScalaC++, JavaScript
Server operating systemshostedLinux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyesyes
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 indexesyesall fields are automatically indexedno
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Java
PHP
Java
Scala
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresTransact SQLnonoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno 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 dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlyesnoyes

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More resources
Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbSpark SQLWakandaDB
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