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DBMS > Bangdb vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. PlanetScale

System Properties Comparison Bangdb vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. PlanetScale

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphDistributed Event Store optimized for Internet of Things use casesElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Event Store
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial 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
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Websitebangdb.comwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­synapse-analyticsplanetscale.com
Technical documentationdocs.bangdb.comwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­azure/­synapse-analyticsplanetscale.com/­docs
DeveloperSachin Sinha, BangDBIBMMicrosoftPlanetScale
Initial release2012201720162020
Current releaseBangDB 2.0, October 20212.0
License infoCommercial or Open SourceOpen Source infoBSD 3commercial infofree developer edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C and C++C++Go
Server operating systemsLinuxLinux infoLinux, macOS, Windows for the developer additionhostedDocker
Linux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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, geospatialnoyesyes
SQL infoSupport of SQLSQL like support with command line toolyes infothrough the embedded Spark runtimeyesyes infowith proprietary extensions
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Java
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C#
Java
PHP
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyesTransact SQLyes infoproprietary syntax
Triggersyes, Notifications (with Streaming only)nonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Active-active shard replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlNo - written data is immutableyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
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 modeyesyes
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardyesUsers with fine-grained authorization concept infono user groups or roles

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More resources
BangdbIBM Db2 Event StoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehousePlanetScale
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