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DBMS > Bangdb vs. Dgraph vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. PostgreSQL

System Properties Comparison Bangdb vs. Dgraph vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. PostgreSQL

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDgraph  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphDistributed and scalable native Graph DBMSCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Fully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Graph DBMSDocument storeRelational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsSpatial DBMSDocument 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
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitebangdb.comdgraph.iofirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerwww.postgresql.org
Technical documentationdocs.bangdb.comdgraph.io/­docsfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docs
DeveloperSachin Sinha, BangDBDgraph Labs, Inc.GoogleMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20122016201720191989 info1989: Postgres, 1996: PostgreSQL
Current releaseBangDB 2.0, October 2021cloud service with continuous releases16.3, May 2024
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache 2.0commercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++GoC
Server operating systemsLinuxLinux
OS X
Windows
hostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL like support with command line toolnonoKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensions
APIs and other access methodsProprietary protocol
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnonoyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyes, Notifications (with Streaming only)noyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmyesShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Synchronous replication via RaftMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
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 modenono
User concepts infoAccess controlyes (enterprise version only)no infoPlanned for future releasesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Azure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
BangdbDgraphGoogle Cloud FirestoreMicrosoft Azure Data ExplorerPostgreSQL
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