DBMS > Apache Druid vs. Microsoft Access vs. RethinkDB vs. Snowflake vs. SwayDB

System Properties Comparison Apache Druid vs. Microsoft Access vs. RethinkDB vs. Snowflake vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.)

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

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Trend Chart

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

druid.apache.org

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

rethinkdb.com

www.snowflake.com

swaydb.simer.au

Technical documentation

druid.apache.org/docs/latest/design

developer.microsoft.com/en-us/access

rethinkdb.com/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Microsoft

The Linux Foundation

since July 2017

Snowflake Computing Inc.

Simer Plaha

Initial release

2012

1992

2009

2014

2018

Current release

29.0.1, April 2024

1902 (16.0.11328.20222), March 2019

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Scala

Server operating systems

Linux
OS X
Unix

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Windows

hosted

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

but not compliant to any SQL standard

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript (Node.js)
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

Client-side triggers through changefeeds

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

range based

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Atomic single-document operations

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

yes

users and table-level permissions

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

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