DBMS > Amazon DocumentDB vs. Fujitsu Enterprise Postgres vs. RocksDB vs. TempoIQ

System Properties Comparison Amazon DocumentDB vs. Fujitsu Enterprise Postgres vs. RocksDB vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

aws.amazon.com/documentdb

www.postgresql.fastware.com

rocksdb.org

tempoiq.com (offline)

Technical documentation

aws.amazon.com/documentdb/resources

www.postgresql.fastware.com/product-manuals

github.com/facebook/rocksdb/wiki

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Facebook, Inc.

TempoIQ

Initial release

2019

2013

2012

Current release

Fujitsu Enterprise Postgres 14, January 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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

C++ API
Java API

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

partitioning by range, list and by hash

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

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

Atomic single-document operations

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

simple authentication-based access control

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