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DBMS > Amazon Redshift vs. Bangdb vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Amazon Redshift vs. Bangdb vs. Microsoft Azure Synapse Analytics vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonBangdb  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsConverged and high performance database for device data, events, time series, document and graphElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftbangdb.comazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftdocs.bangdb.comdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)Sachin Sinha, BangDBMicrosoftApache Software Foundation
Initial release2012201220162014
Current releaseBangDB 2.0, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD 3commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++C++Scala
Server operating systemshostedLinuxhostedLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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 indexesrestrictedyes infosecondary, composite, nested, reverse, geospatialyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL like support with command line toolyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PythonnoTransact SQLno
Triggersnoyes, Notifications (with Streaming only)nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor, Knob for CAP (enterprise version only)yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnono 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 dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modeno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes (enterprise version only)yesno

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More resources
Amazon RedshiftBangdbMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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