DBMS > Atos Standard Common Repository vs. Rockset vs. SiteWhere vs. Vertica

System Properties Comparison Atos Standard Common Repository vs. Rockset vs. SiteWhere vs. Vertica

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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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

M2M integration platform for persisting/querying time series data

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Relational DBMS
Search engine

Spatial DBMS
Time Series DBMS

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

Score	1.07
Rank	#180	Overall
	#31	Document stores

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

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

rockset.com

github.com/sitewhere/sitewhere

www.vertica.com

Technical documentation

docs.rockset.com

sitewhere1.sitewhere.io/index.html

vertica.com/documentation

Developer

Atos Convergence Creators

Rockset

SiteWhere

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2019

2010

2005

Current release

1703

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Java

C++

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

predefined scheme

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

optional

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Read-only SQL queries, including JOINs

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

LDAP

HTTP REST

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

All languages with LDAP bindings

Go
Java
JavaScript (Node.js)
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic sharding

Sharding

based on HBase

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

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

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 and organizations can be defined via Rockset console

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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