DBMS > Atos Standard Common Repository vs. GeoSpock vs. Google BigQuery vs. Microsoft Access vs. XTDB

System Properties Comparison Atos Standard Common Repository vs. GeoSpock vs. Google BigQuery vs. Microsoft Access vs. XTDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Spatial and temporal data processing engine for extreme data scale

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.)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Secondary database models

Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

geospock.com

cloud.google.com/bigquery

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

www.xtdb.com/docs

Developer

Atos Convergence Creators

GeoSpock

Google

Microsoft

Juxt Ltd.

Initial release

2016

2010

1992

2019

Current release

1703

2.0, September 2019

1902 (16.0.11328.20222), March 2019

1.19, September 2021

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

MIT License

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

Java, Javascript

C++

Clojure

Server operating systems

Linux

hosted

Windows

Not a real database server, but making use of DLLs

All OS with a Java 8 (and higher) VM
Linux

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

yes, extensible-data-notation format

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

but not compliant to any SQL standard

limited SQL, making use of Apache Calcite

APIs and other access methods

LDAP

JDBC

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

HTTP REST
JDBC

Supported programming languages

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

Since BigQuery is designed for querying 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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

LDAP bind authentication

Access rights for users can be defined per table

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

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