DBMS > atoti vs. Google BigQuery vs. Microsoft Access vs. Newts vs. OpenTenBase

System Properties Comparison atoti vs. Google BigQuery vs. Microsoft Access vs. Newts vs. OpenTenBase

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Large scale data warehouse service with append-only tables

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.)

Time Series DBMS based on Cassandra

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

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Trend Chart

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

atoti.io

cloud.google.com/bigquery

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

opennms.github.io/newts

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

docs.atoti.io

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

github.com/OpenNMS/newts/wiki

docs.opentenbase.org
docs.opentenbase.org/en

Developer

ActiveViam

Google

Microsoft

OpenNMS Group

OpenAtom Foundation, previously Tencent

Initial release

2010

1992

2014

Current release

1902 (16.0.11328.20222), March 2019

2.5, January 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Bundled with Microsoft Office

Open Source

Apache 2.0

Open Source

BSD-3

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

Java

C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

but not compliant to any SQL standard

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

HTTP REST
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Java

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

Python

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (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

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

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

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