DBMS > Amazon DynamoDB vs. Datomic vs. EXASOL vs. Percona Server for MongoDB vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. Datomic vs. EXASOL vs. Percona Server for MongoDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/dynamodb

www.datomic.com

www.exasol.com

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.datomic.com

www.exasol.com/resources

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

Developer

Amazon

Cognitect

Exasol

Percona

Snowflake Computing Inc.

Initial release

2012

2000

2015

2014

Current release

1.0.6735, June 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

limited edition free

commercial

Open Source

GPL Version 2

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, Clojure

C++

Server operating systems

hosted

All OS with a Java VM

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes

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

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java

Java
Lua
Python
R

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

JavaScript

user defined functions

Triggers

yes

by integration with AWS Lambda

By using transaction functions

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

via In-Memory Engine

User concepts

Access control

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

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

Access rights for users and roles

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

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