DBMS > Atos Standard Common Repository vs. Google BigQuery vs. Microsoft Access vs. Sphinx vs. VictoriaMetrics

System Properties Comparison Atos Standard Common Repository vs. Google BigQuery vs. Microsoft Access vs. Sphinx vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

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

Description

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

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.)

Open source search engine for searching in data from different sources, e.g. relational databases

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store
Key-value store

Relational DBMS

Search engine

Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

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

cloud.google.com/bigquery

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

sphinxsearch.com

victoriametrics.com

Technical documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

sphinxsearch.com/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Atos Convergence Creators

Google

Microsoft

Sphinx Technologies Inc.

VictoriaMetrics

Initial release

2016

2010

1992

2001

2018

Current release

1703

1902 (16.0.11328.20222), March 2019

3.5.1, February 2023

v1.91, May 2023

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 2.0

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++

Server operating systems

Linux

hosted

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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

full-text index on all search fields

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language (SphinxQL)

APIs and other access methods

LDAP

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Proprietary protocol

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Synchronous replication

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

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

The original contents of fields are not stored in the Sphinx index.

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

LDAP bind authentication

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.