DBMS > MongoDB vs. Newts vs. Quasardb vs. VictoriaMetrics

System Properties Comparison MongoDB vs. Newts vs. Quasardb vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store

Time Series DBMS

Secondary database models

Spatial DBMS
Search engine

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

Time Series Collections introduced in Release 5.0

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

Score	478.24
Rank	#5	Overall
	#1	Document stores

Score	0.00
Rank	#354	Overall
	#33	Time Series DBMS

Score	0.11
Rank	#310	Overall
	#28	Time Series DBMS

Score	0.58
Rank	#223	Overall
	#17	Time Series DBMS

Website

www.mongodb.com

opennms.github.io/newts

quasardb.net

victoriametrics.com

Technical documentation

docs.mongodb.com/manual

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

MongoDB, Inc

OpenNMS Group

quasardb

VictoriaMetrics

Initial release

2009

2014

2009

2018

Current release

5.0.8, April 2022

3.13.3, April 2022

v1.72, January 2022

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database 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.
ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.

Implementation language

C++

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

BSD
Linux
OS X
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

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.

schema-free

Typing

predefined data types such as float or date

yes

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

yes

integer and binary

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.

Secondary indexes

yes

with tags

SQL

Support of SQL

Read-only SQL queries via the MongoDB Connector for BI

SQL-like query language

APIs and other access methods

proprietary protocol using JSON

HTTP REST
Java API

HTTP API

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

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
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

Java

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

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

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.

Sharding

based on Cassandra

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

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

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

by using LevelDB

yes

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

yes

Transient mode

User concepts

Access control

Access rights for users and roles

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

MongoDB’s application data platform provides developers a unified interface to power...
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High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
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High performance, horizontally scalable time series database and monitoring solution...
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Competitive advantages

The MongoDB platform can be used by developers building transactional, operational,...
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High performance in a cost-effective small package Real-time results for even large...
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Specifically designed for highly loaded workloads Addresses most of the scalability...
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Typical application scenarios

Internet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more

Tick database Predictive maintenance Pre-deal checks Large scale monitoring
» more

When the current monitoring solution can't keep up with increasing workload Kubernetes...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Large EU investment banks US based hedge funds Orolia Tellmeplus
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Grammarly, Wix.com, adidas, Sensedia, Brandwatch, CERN, COLOPL, Razorpay See our...
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Market metrics

200+ million downloads, over 1.5M Atlas database clusters under management handling...
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Has been running in very demanding production environments since 2013 Rapid adoption...
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6k stars and 100+ contributors on GitHub 45M+ downloads Thousands of active users...
» more

Licensing and pricing models

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

Community edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

VictoriaMetrics comes in three versions: an open source version, an Enterprise version...
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