DBMS > Kinetica vs. Oracle Berkeley DB vs. Snowflake vs. SQL.JS

System Properties Comparison Kinetica vs. Oracle Berkeley DB vs. Snowflake vs. SQL.JS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Widely used in-process key-value store

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

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

www.kinetica.com

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

www.snowflake.com

sql.js.org

Technical documentation

docs.kinetica.com

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

docs.snowflake.net/manuals/index.html

sql.js.org/documentation/index.html

Developer

Kinetica

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

Alon Zakai

enhancements implemented by others

Initial release

2012

1994

2014

2012

Current release

7.1, August 2021

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

commercial

Open Source

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, C++

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

JavaScript

Server operating systems

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

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

SQL-like DML and DDL statements

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

JavaScript API

Supported programming languages

C++
Java
JavaScript (Node.js)
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

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

only for the SQL API

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

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

except by serializing a db to a file

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

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

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.