DBMS > JSqlDb vs. Oracle Berkeley DB vs. Snowflake vs. Transwarp KunDB

System Properties Comparison JSqlDb vs. Oracle Berkeley DB vs. Snowflake vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

JavaScript Query Language Database, stores JavaScript objects and primitives

Widely used in-process key-value store

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Document store
Object oriented DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

jsqldb.org (offline)

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

www.snowflake.com

www.transwarp.cn/en/product/kundb

Technical documentation

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

docs.snowflake.net/manuals/index.html

Developer

Konrad von Backstrom

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

Transwarp

Initial release

2018

1994

2014

Current release

0.8, December 2018

18.1.40, May 2020

License

Commercial or Open Source

Open Source

commercial license 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)

Server operating systems

Linux
macOS
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Data scheme

schema-free

yes

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

yes

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.

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

APIs and other access methods

CLI Client
JDBC
ODBC

Supported programming languages

JavaScript

.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

Server-side scripts

Stored procedures

functions in JavaScript

user defined functions

yes

Triggers

yes

only for the SQL API

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

yes

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