DBMS > CockroachDB vs. EsgynDB vs. MongoDB vs. Sadas Engine vs. Solr

System Properties Comparison CockroachDB vs. EsgynDB vs. MongoDB vs. Sadas Engine vs. Solr

Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

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
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Spatial DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.cockroachlabs.com

Technical documentation

www.cockroachlabs.com/docs

www.mongodb.com/docs/manual

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

solr.apache.org/resources.html

Developer

Cockroach Labs

Esgyn

MongoDB, Inc

SADAS s.r.l.

Apache Software Foundation

Initial release

2015

2009

2006

Current release

23.1.1, May 2023

6.0.7, June 2023

8.0

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

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.

commercial

free trial version available

Open Source

Apache Version 2

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.

Implementation language

C++, Java

C++

Java

Server operating systems

Linux
macOS
Windows

Linux

Linux
OS X
Solaris
Windows

AIX
Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

dynamic schema

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.

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

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

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

Solr Parallel SQL Interface

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
ODBC
Proprietary protocol

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

JavaScript

Java plugins

Triggers

yes

in MongoDB Atlas only

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

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.

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication between multi datacenters

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

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

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

Licensing and pricing models

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.