DBMS > CockroachDB vs. Datastax Enterprise vs. MongoDB vs. Solr vs. YugabyteDB

System Properties Comparison CockroachDB vs. Datastax Enterprise vs. MongoDB vs. Solr vs. YugabyteDB

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.

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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

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

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector 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

Spatial DBMS

Document store
Wide column store

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

Score	6.10
Rank	#58	Overall
	#33	Relational DBMS

Score	6.31
Rank	#57	Overall
	#4	Wide column stores

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	44.28
Rank	#24	Overall
	#3	Search engines

Score	3.11
Rank	#99	Overall
	#51	Relational DBMS

Website

www.cockroachlabs.com

www.datastax.com/products/datastax-enterprise

www.mongodb.com

solr.apache.org

www.yugabyte.com

Technical documentation

www.cockroachlabs.com/docs

docs.datastax.com

www.mongodb.com/docs/manual

solr.apache.org/resources.html

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Cockroach Labs

DataStax

MongoDB, Inc

Apache Software Foundation

Yugabyte Inc.

Initial release

2015

2011

2009

2006

2017

Current release

23.1.1, May 2023

6.8, April 2020

6.0.7, June 2023

9.5.0, February 2024

2.19, September 2023

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.

Open Source

Apache Version 2

Open Source

Apache 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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java

C++

Java

C and C++

Server operating systems

Linux
macOS
Windows

Linux
OS X

Linux
OS X
Solaris
Windows

All OS with a Java VM

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

Linux
OS X

Data scheme

dynamic schema

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

depending on used data model

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

yes

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

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like DML and DDL statements (CQL); Spark SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

Solr Parallel SQL Interface

yes, PostgreSQL compatible

APIs and other access methods

JDBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

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

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

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

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

Server-side scripts

Stored procedures

JavaScript

Java plugins

yes

sql, plpgsql, C

Triggers

yes

in MongoDB Atlas only

yes

User configurable commands triggered on index changes

yes

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

no "single point of failure"

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

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

configurable replication factor, datacenter aware, advanced replication for edge computing

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

yes

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

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

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Strong consistency on writes and tunable consistency on reads

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

Atomicity and isolation are supported for single operations

Multi-document ACID Transactions with snapshot isolation

optimistic locking

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

based on RocksDB

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

User concepts

Access control

Role-based access control

Access rights for users can be defined per object

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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YugabyteDB is an open source distributed SQL database for cloud native transactional...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Systems of record and engagement for cloud native applications that require resilience,...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

Annual subscription
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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Apache 2.0 license for the database
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.