DBMS > Bangdb vs. Couchbase vs. Graphite vs. Microsoft Azure Data Explorer vs. MongoDB

System Properties Comparison Bangdb vs. Couchbase vs. Graphite vs. Microsoft Azure Data Explorer vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Fully managed big data interactive analytics platform

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Graph DBMS
Time Series DBMS

column oriented

Secondary database models

Spatial DBMS

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store

If 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

this 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

support 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

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

bangdb.com

www.couchbase.com

github.com/graphite-project/graphite-web

azure.microsoft.com/services/data-explorer

www.mongodb.com

Technical documentation

docs.bangdb.com

docs.couchbase.com

graphite.readthedocs.io

docs.microsoft.com/en-us/azure/data-explorer

www.mongodb.com/docs/manual

Developer

Sachin Sinha, BangDB

Couchbase, Inc.

Chris Davis

Microsoft

MongoDB, Inc

Initial release

2012

2011

2006

2019

2009

Current release

BangDB 2.0, October 2021

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

cloud service with continuous releases

6.0.7, June 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C, C++

C, C++, Go and Erlang

Python

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
Unix

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

Although 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.

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

Numeric data only

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

Kusto Query Language (KQL), SQL subset

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

HTTP API
Sockets

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C
C#
C++
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Yes, possible languages: KQL, Python, R

JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

via the TAP protocol

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Automatic Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

including cross data center replication
Source-replica replication

none

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

locking

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

optional, enabled by default

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

Ephemeral buckets

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

yes (enterprise version only)

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Azure Active Directory Authentication

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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