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DBMS > Bangdb vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Data Explorer vs. MongoDB vs. WakandaDB

System Properties Comparison Bangdb vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Data Explorer vs. MongoDB vs. WakandaDB

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMongoDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Fully managed big data interactive analytics platformOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument storeObject oriented DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
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
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitebangdb.comwww.postgresql.fastware.comazure.microsoft.com/­services/­data-explorerwww.mongodb.comwakanda.github.io
Technical documentationdocs.bangdb.comwww.postgresql.fastware.com/­product-manualsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.mongodb.com/­docs/­manualwakanda.github.io/­doc
DeveloperSachin Sinha, BangDBPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyMicrosoftMongoDB, IncWakanda SAS
Initial release2012201920092012
Current releaseBangDB 2.0, October 2021Fujitsu Enterprise Postgres 14, January 2022cloud service with continuous releases6.0.7, June 20232.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
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Implementation languageC, C++CC++C++, JavaScript
Server operating systemsLinuxLinux
Windows
hostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.yes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes
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.noyesno
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL like support with command line toolyesKusto Query Language (KQL), SQL subsetRead-only SQL queries via the MongoDB Atlas SQL Interfaceno
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
JavaScript
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, RJavaScriptyes
Triggersyes, Notifications (with Streaming only)yesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoin MongoDB Atlas onlyyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmpartitioning by range, list and by hashSharding infoImplicit feature of the cloud serviceSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.none
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate Consistency
Foreign keys infoReferential integritynoyesnono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoMulti-document ACID Transactions with snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes infooptional, enabled by defaultyes
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 modenoyes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights for users and rolesyes
More information provided by the system vendor
BangdbFujitsu Enterprise PostgresMicrosoft Azure Data ExplorerMongoDBWakandaDB
Specific characteristics100% compatible with community PostgreSQL
» more
MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Built around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsCore based licensing
» more
MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
BangdbFujitsu Enterprise PostgresMicrosoft Azure Data ExplorerMongoDBWakandaDB
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