DBMS > Amazon DocumentDB vs. Oracle Berkeley DB vs. RethinkDB vs. TempoIQ

System Properties Comparison Amazon DocumentDB vs. Oracle Berkeley DB vs. RethinkDB 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

Widely used in-process key-value store

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

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

Primary database model

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

aws.amazon.com/documentdb

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

rethinkdb.com

tempoiq.com (offline)

Technical documentation

aws.amazon.com/documentdb/resources

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

rethinkdb.com/docs

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

The Linux Foundation

since July 2017

TempoIQ

Initial release

2019

1994

2009

2012

Current release

18.1.40, May 2020

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache Version 2

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

C++

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.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

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#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Client-side triggers through changefeeds

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

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

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

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

Transaction concepts

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

Atomic single-document operations

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

yes

users and table-level permissions

simple authentication-based access control

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