DBMS > Linter vs. Microsoft Access vs. Oracle Berkeley DB vs. SiriDB vs. Snowflake

System Properties Comparison Linter vs. Microsoft Access vs. Oracle Berkeley DB vs. SiriDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used in-process key-value store

Open Source Time Series DBMS

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

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

linter.ru

www.microsoft.com/en-us/microsoft-365/access

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

siridb.com

www.snowflake.com

Technical documentation

developer.microsoft.com/en-us/access

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

docs.siridb.com

docs.snowflake.net/manuals/index.html

Developer

relex.ru

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Cesbit

Snowflake Computing Inc.

Initial release

1990

1992

1994

2017

2014

Current release

1902 (16.0.11328.20222), March 2019

18.1.40, May 2020

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

commercial license available

Open Source

MIT License

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 and C++

C++

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

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Windows

Not a real database server, but making use of DLLs

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

Numeric data

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

but not compliant to any SQL standard

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
DAO
ODBC
OLE DB

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.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
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

yes

only for the SQL API

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

simple rights management via user accounts

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

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