DBMS > Atos Standard Common Repository vs. EXASOL vs. Google BigQuery vs. Qdrant vs. SpatiaLite

System Properties Comparison Atos Standard Common Repository vs. EXASOL vs. Google BigQuery vs. Qdrant vs. SpatiaLite

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

A high-performance vector database with neural network or semantic-based matching

Spatial extension of SQLite

Primary database model

Document store
Key-value store

Relational DBMS

Vector DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

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

www.exasol.com

cloud.google.com/bigquery

github.com/qdrant/qdrant
qdrant.tech

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

www.exasol.com/resources

cloud.google.com/bigquery/docs

qdrant.tech/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Atos Convergence Creators

Exasol

Google

Qdrant

Alessandro Furieri

Initial release

2016

2000

2010

2021

2008

Current release

1703

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Rust

C++

Server operating systems

Linux

hosted

Docker
Linux
macOS
Windows

server-less

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

APIs and other access methods

LDAP

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

All languages with LDAP bindings

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

Google Cloud Identity & Access Management (IAM)

Key-based authentication

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