DBMS > Databricks vs. Dgraph vs. Manticore Search vs. MongoDB vs. Percona Server for MongoDB

System Properties Comparison Databricks vs. Dgraph vs. Manticore Search vs. MongoDB vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Distributed and scalable native Graph DBMS

Multi-storage database for search, including full-text search.

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Document store
Relational DBMS

Graph DBMS

Search engine

Document store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.60
Rank	#246	Overall
	#39	Document stores

Website

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.databricks.com

dgraph.io/docs

manual.manticoresearch.com

www.mongodb.com/docs/manual

docs.percona.com/percona-distribution-for-mongodb

Developer

Databricks

Dgraph Labs, Inc.

Manticore Software

MongoDB, Inc

Percona

Initial release

2013

2016

2017

2009

2015

Current release

6.0, February 2023

6.0.7, June 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL 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.

Open Source

GPL Version 2

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Fixed 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.

schema-free

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

yes

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

proprietary protocol using JSON

Supported programming languages

Python
R
Scala

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

Synchronous replication based on Galera library

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

Source-replica replication

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

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency
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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

via In-Memory Engine

User concepts

Access control

Planned for future releases

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.