DBMS > Datomic vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. QuestDB

System Properties Comparison Datomic vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.)

Globally distributed, horizontally scalable, multi-model database service

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

www.datomic.com

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

azure.microsoft.com/services/cosmos-db

questdb.io

Technical documentation

docs.datomic.com

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

questdb.io/docs

Developer

Cognitect

Microsoft

QuestDB Technology Inc

Initial release

2012

1992

2014

Current release

1.0.7180, July 2024

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

limited edition free

commercial

Bundled with Microsoft Office

commercial

Open Source

Apache 2.0

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, Clojure

C++

Java (Zero-GC), C++, Rust

Server operating systems

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

SQL with time-series extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

Clojure
Java

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

By using transaction functions

yes

since Access 2010 using the ACE-engine

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Implicit feature of the cloud service

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

Implicit feature of the cloud service

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

through memory mapped files

User concepts

Access control

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

Access rights can be defined down to the item level

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