DBMS > Amazon DynamoDB vs. BigObject vs. GridGain vs. SiriDB vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. BigObject vs. GridGain vs. SiriDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

GridGain is an in-memory computing platform, built on Apache Ignite

Open Source Time Series DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.bigobject.io

www.gridgain.com/docs/index.html

docs.siridb.com

docs.snowflake.net/manuals/index.html

Developer

Amazon

BigObject, Inc.

GridGain Systems, Inc.

Cesbit

Snowflake Computing Inc.

Initial release

2012

2015

2007

2017

2014

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

commercial

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data

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

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

by integration with AWS Lambda

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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)

Security Hooks for custom implementations

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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