DBMS > CockroachDB vs. Faircom DB vs. Memcached vs. MongoDB vs. Trino

System Properties Comparison CockroachDB vs. Faircom DB vs. Memcached vs. MongoDB vs. Trino

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.

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

In-memory key-value store, originally intended for caching

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

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Document store

Relational 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
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.cockroachlabs.com

www.faircom.com/products/faircom-db

www.memcached.org

www.mongodb.com

trino.io

Technical documentation

www.cockroachlabs.com/docs

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

github.com/memcached/memcached/wiki

www.mongodb.com/docs/manual

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Cockroach Labs

FairCom Corporation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

MongoDB, Inc

Trino Software Foundation

Initial release

2015

1979

2003

2009

2012

2020 rebranded from PrestoSQL

Current release

23.1.1, May 2023

V12, November 2020

1.6.25, March 2024

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Restricted, free version available

Open Source

BSD license

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 2.0

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.
MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

ANSI C, C++

C++

Java

Server operating systems

Linux
macOS
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

FreeBSD
Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

dynamic schema

schema free, schema optional, schema required, partial 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

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

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

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.

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes, ANSI SQL with proprietary extensions

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

JDBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Proprietary protocol

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

JavaScript

yes, depending on connected data-source

Triggers

yes

in MongoDB Atlas only

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

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

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.

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

Repcached, a Memcached patch, provides this functionallity

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

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

depending on connected data-source

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

ACID

tunable from ACID to Eventually Consistent

Multi-document ACID Transactions with snapshot isolation

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

optional, enabled by default

depending on connected data-source

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

Role-based access control

Fine grained access rights according to SQL-standard with additional protections for files

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

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

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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.