DBMS > Datomic vs. Fujitsu Enterprise Postgres vs. MongoDB vs. RRDtool vs. SAP HANA

System Properties Comparison Datomic vs. Fujitsu Enterprise Postgres vs. MongoDB vs. RRDtool vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Document store
Spatial 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

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.datomic.com

www.postgresql.fastware.com

www.mongodb.com

oss.oetiker.ch/rrdtool

www.sap.com/products/hana.html

Technical documentation

docs.datomic.com

www.postgresql.fastware.com/product-manuals

www.mongodb.com/docs/manual

oss.oetiker.ch/rrdtool/doc

help.sap.com/hana

Developer

Cognitect

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

MongoDB, Inc

Tobias Oetiker

SAP

Initial release

2012

2009

1999

2010

Current release

1.0.7075, December 2023

Fujitsu Enterprise Postgres 14, January 2022

6.0.7, June 2023

1.8.0, 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

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 V2 and FLOSS

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
OS X
Solaris
Windows

HP-UX
Linux

Appliance or cloud-service

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.

yes

Typing

predefined data types such as float or date

yes

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

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

in-process shared library
Pipes

JDBC
ODBC

Supported programming languages

Clojure
Java

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

JavaScript

SQLScript, R

Triggers

By using transaction functions

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

partitioning by range, list and by hash

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

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

none

yes

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

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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