DBMS > Amazon DynamoDB vs. Atos Standard Common Repository vs. GigaSpaces vs. TigerGraph

System Properties Comparison Amazon DynamoDB vs. Atos Standard Common Repository vs. GigaSpaces vs. TigerGraph

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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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

aws.amazon.com/dynamodb

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

www.gigaspaces.com

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.gigaspaces.com/latest/landing.html

docs.tigergraph.com

Developer

Amazon

Atos Convergence Creators

Gigaspaces Technologies

Initial release

2012

2016

2000

2017

Current release

1703

15.5, September 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

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, C++, .Net

C++

Server operating systems

hosted

Linux

Linux
macOS
Solaris
Windows

Linux

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

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

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

LDAP

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages with LDAP bindings

.Net
C++
Java
Python
Scala

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

LDAP bind authentication

Role-based access control

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