DBMS > Oracle Berkeley DB vs. Snowflake vs. SQream DB vs. SWC-DB vs. UniData,UniVerse

System Properties Comparison Oracle Berkeley DB vs. Snowflake vs. SQream DB vs. SWC-DB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Widely used in-process key-value store

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

a GPU-based, columnar RDBMS for big data analytics workloads

A high performance, scalable Wide Column DBMS

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

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Wide column store

Multivalue DBMS

Secondary database models

Time Series DBMS

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

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

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

www.snowflake.com

sqream.com

github.com/kashirin-alex/swc-db
www.swcdb.org

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

Technical documentation

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

docs.snowflake.net/manuals/index.html

docs.sqream.com

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

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

SQream Technologies

Alex Kashirin

Rocket Software

Initial release

1994

2014

2017

2020

1985

Current release

18.1.40, May 2020

2022.1.6, December 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

commercial license available

commercial

Open Source

GPL V3

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++, CUDA, Haskell, Java, Scala

C++

Server operating systems

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL-like query language

yes

APIs and other access methods

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Proprietary protocol
Thrift

Java API

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

Supported programming languages

.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++
Java
JavaScript (Node.js)
Python

C++

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

user defined functions in Python

yes

Triggers

yes

only for the SQL API

similar concept for controling cloud resources

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

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

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

Access rights according to SQL-standard and operating system based

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