DBMS > JaguarDB vs. MongoDB vs. Oracle Berkeley DB vs. Snowflake vs. Splice Machine

System Properties Comparison JaguarDB vs. MongoDB vs. Oracle Berkeley DB vs. Snowflake vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

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

Widely used in-process key-value store

Cloud-based data warehousing service for structured and semi-structured data

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Key-value store
Vector DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

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

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.jaguardb.com

www.mongodb.com

www.oracle.com/database/technologies/related/berkeleydb.html

www.snowflake.com

splicemachine.com

Technical documentation

www.jaguardb.com/support.html

www.mongodb.com/docs/manual

docs.oracle.com/cd/E17076_05/html/index.html

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

Developer

DataJaguar, Inc.

MongoDB, Inc

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

Splice Machine

Initial release

2015

2009

1994

2014

Current release

3.3 July 2023

6.0.7, June 2023

18.1.40, May 2020

3.1, March 2021

License

Commercial or Open Source

Open Source

GPL V3.0

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

commercial license available

commercial

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

yes

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.
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Implementation language

C++

the server part. Clients available in other languages

C++

C, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

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.

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
ODBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

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

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

JavaScript

user defined functions

yes

Java

Triggers

yes

in MongoDB Atlas only

yes

only for the SQL API

similar concept for controling cloud resources

yes

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.

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

rights management via user accounts

Access rights for users and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users, groups and roles according to SQL-standard

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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