DBMS > Ingres vs. Microsoft Access vs. Riak KV vs. Sadas Engine vs. Snowflake

System Properties Comparison Ingres vs. Microsoft Access vs. Riak KV vs. Sadas Engine vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

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.)

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.actian.com/databases/ingres

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

www.sadasengine.com

www.snowflake.com

Technical documentation

docs.actian.com/ingres

developer.microsoft.com/en-us/access

www.tiot.jp/riak-docs/riak/kv/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.snowflake.net/manuals/index.html

Developer

Actian Corporation

Microsoft

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Snowflake Computing Inc.

Initial release

1974

originally developed at University Berkely in early 1970s

1992

2009

2006

2014

Current release

11.2, May 2022

1902 (16.0.11328.20222), March 2019

3.2.0, December 2022

8.0

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version 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++

Erlang

C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

Linux
OS X

AIX
Linux
Windows

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

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
DAO
ODBC
OLE DB

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Erlang

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Sharding

no "single point of failure"

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

none

selectable replication factor

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

MVCC

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes, using Riak Security

Access rights for users, groups and roles according to SQL-standard

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

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