DBMS > Amazon DynamoDB vs. Oracle Berkeley DB vs. Sphinx vs. UniData,UniVerse

System Properties Comparison Amazon DynamoDB vs. Oracle Berkeley DB vs. Sphinx vs. UniData,UniVerse

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Widely used in-process key-value store

Open source search engine for searching in data from different sources, e.g. relational databases

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Document store
Key-value store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Search engine

Multivalue DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

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

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

aws.amazon.com/dynamodb

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

sphinxsearch.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.aws.amazon.com/dynamodb

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

sphinxsearch.com/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Sphinx Technologies Inc.

Rocket Software

Initial release

2012

1994

2001

1985

Current release

18.1.40, May 2020

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

commercial license available

Open Source

GPL version 2, commercial licence available

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL-like query language (SphinxQL)

yes

APIs and other access methods

RESTful HTTP API

Proprietary protocol

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

only for the SQL API

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Source-replica replication

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

configurable

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 Sphinx index.

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 can be defined via the AWS Identity and Access Management (IAM)

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.