DBMS > atoti vs. Google Cloud Bigtable vs. Kdb vs. Microsoft SQL Server vs. MongoDB

System Properties Comparison atoti vs. Google Cloud Bigtable vs. Kdb vs. Microsoft SQL Server vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

High performance Time Series DBMS

Microsofts flagship relational DBMS

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

Object oriented DBMS

Key-value store
Wide column store

Time Series DBMS
Vector DBMS

Relational DBMS

Document store

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Website

atoti.io

cloud.google.com/bigtable

kx.com

www.microsoft.com/en-us/sql-server

www.mongodb.com

Technical documentation

docs.atoti.io

cloud.google.com/bigtable/docs

code.kx.com

learn.microsoft.com/en-US/sql/sql-server

www.mongodb.com/docs/manual

Developer

ActiveViam

Google

Kx Systems, a division of First Derivatives plc

Microsoft

MongoDB, Inc

Initial release

2015

2000

kdb was released 2000, kdb+ in 2003

1989

2009

Current release

3.6, May 2018

SQL Server 2022, November 2022

6.0.7, June 2023

License

Commercial or Open Source

commercial

free versions available

commercial

free 32-bit version

commercial

restricted free version is available

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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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.

Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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, 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

table attribute 'grouped'

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (q)

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Python

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

JavaScript

Triggers

yes

with views

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

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

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

yes, but depending on the SQL-Server Edition

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-row operations

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

rights management via user accounts

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

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

tick database streaming sensor data massive intelligence applications oil and gas...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

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