DBMS > Elasticsearch vs. Heroic vs. MongoDB vs. RethinkDB vs. Speedb

System Properties Comparison Elasticsearch vs. Heroic vs. MongoDB vs. RethinkDB vs. Speedb

Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

Primary database model

Secondary database models

Document store
Spatial DBMS
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

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.21
Rank	#315	Overall
	#45	Key-value stores

Website

www.elastic.co/elasticsearch

github.com/spotify/heroic

www.mongodb.com

rethinkdb.com

www.speedb.io

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

spotify.github.io/heroic

www.mongodb.com/docs/manual

rethinkdb.com/docs

Developer

Elastic

Spotify

MongoDB, Inc

The Linux Foundation

since July 2017

Speedb

Initial release

2010

2014

2009

2020

Current release

8.6, January 2023

6.0.7, June 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

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 Version 2.0; commercial license available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

string, binary, float, bool, date, geometry

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

All search fields are automatically indexed

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Java API
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

by using the 'percolation' feature

yes

in MongoDB Atlas only

Client-side triggers through changefeeds

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

range based

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate 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

Atomic single-document operations

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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.

Memcached and Redis integration

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights for users and roles

yes

users and table-level permissions

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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Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
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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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Open source - Speedb OSS is released under an Apache license and can be found on...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.