DBMS > CockroachDB vs. Geode vs. Hive vs. LokiJS vs. MongoDB

System Properties Comparison CockroachDB vs. Geode vs. Hive vs. LokiJS vs. MongoDB

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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

data warehouse software for querying and managing large distributed datasets, built on Hadoop

In-memory JavaScript 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

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

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

www.cockroachlabs.com

geode.apache.org

hive.apache.org

github.com/techfort/LokiJS

www.mongodb.com

Technical documentation

www.cockroachlabs.com/docs

geode.apache.org/docs

cwiki.apache.org/confluence/display/Hive/Home

techfort.github.io/LokiJS

www.mongodb.com/docs/manual

Developer

Cockroach Labs

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Apache Software Foundation

initially developed by Facebook

MongoDB, Inc

Initial release

2015

2002

2012

2014

2009

Current release

23.1.1, May 2023

1.1, February 2017

3.1.3, April 2022

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2

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

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

Java

JavaScript

C++

Server operating systems

Linux
macOS
Windows

All OS with a Java VM

the JDK (8 or later) is also required

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Solaris
Windows

Data scheme

dynamic schema

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language (OQL)

SQL-like DML and DDL statements

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
Thrift

JavaScript API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

C++
Java
PHP
Python

JavaScript

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

user defined functions

yes

user defined functions and integration of map-reduce

View functions in JavaScript

JavaScript

Triggers

yes

Cache Event Listeners

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

Sharding

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication

selectable replication factor

none

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

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

ACID

yes, on a single node

atomic operations within a single collection possible

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Role-based access control

Access rights per client and object definable

Access rights for users, groups and roles

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

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

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

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

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