DBMS > Atos Standard Common Repository vs. GigaSpaces vs. InfluxDB vs. MongoDB vs. Vertica

System Properties Comparison Atos Standard Common Repository vs. GigaSpaces vs. InfluxDB vs. MongoDB vs. Vertica

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 data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

DBMS for storing time series, events and metrics

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Document store

Relational DBMS

Column oriented

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

with GEO package

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Spatial DBMS
Time Series DBMS

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

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Score	410.24
Rank	#5	Overall
	#1	Document stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

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

www.gigaspaces.com

www.influxdata.com/products/influxdb-overview

www.mongodb.com

www.vertica.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.influxdata.com/influxdb

www.mongodb.com/docs/manual

vertica.com/documentation

Developer

Atos Convergence Creators

Gigaspaces Technologies

MongoDB, Inc

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2000

2013

2009

2005

Current release

1703

15.5, September 2020

2.7.6, April 2024

7.0.5, January 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

MIT-License; commercial enterprise version available

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Java

Java, C++, .Net

C++

Server operating systems

Linux

Linux
macOS
Solaris
Windows

Linux
OS X

through Homebrew

Linux
OS X
Solaris
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

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

yes

Numeric data and Strings

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

XML can be used for describing objects metadata

Secondary indexes

yes

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

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

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

APIs and other access methods

LDAP

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP API
JSON over UDP

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

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

.Net
C++
Java
Python
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

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

Server-side scripts

Stored procedures

yes

JavaScript

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, event driven architecture

yes

in MongoDB Atlas only

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

in enterprise version only

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

in enterprise version only

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

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

yes

Map-Reduce pattern can be built with XAP task executors

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

LDAP bind authentication

Role-based access control

simple rights management via user accounts

Access rights for users and roles

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

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