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DBMS > Bangdb vs. Datastax Enterprise vs. Microsoft Azure Synapse Analytics

System Properties Comparison Bangdb vs. Datastax Enterprise vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Wide column storeRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score5.80
Rank#60  Overall
#4  Wide column stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitebangdb.comwww.datastax.com/­products/­datastax-enterpriseazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.bangdb.comdocs.datastax.comdocs.microsoft.com/­azure/­synapse-analytics
DeveloperSachin Sinha, BangDBDataStaxMicrosoft
Initial release201220112016
Current releaseBangDB 2.0, October 20216.8, April 2020
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageC, C++JavaC++
Server operating systemsLinuxLinux
OS X
hosted
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: 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.nonono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like DML and DDL statements (CQL); Spark SQLyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
Server-side scripts infoStored proceduresnonoTransact SQL
Triggersyes, Notifications (with Streaming only)yesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infono "single point of failure"Sharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)configurable replication factor, datacenter aware, advanced replication for edge computingyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyes, 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.yes, run db with in-memory only modeyes
User concepts infoAccess controlyes (enterprise version only)Access rights for users can be defined per objectyes
More information provided by the system vendor
BangdbDatastax EnterpriseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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BangdbDatastax EnterpriseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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