DBMS > Amazon DynamoDB vs. Netezza vs. RavenDB vs. Snowflake vs. XTDB

System Properties Comparison Amazon DynamoDB vs. Netezza vs. RavenDB vs. Snowflake vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/dynamodb

www.ibm.com/products/netezza

ravendb.net

www.snowflake.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

ravendb.net/docs

docs.snowflake.net/manuals/index.html

www.xtdb.com/docs

Developer

Amazon

IBM

Hibernating Rhinos

Snowflake Computing Inc.

Juxt Ltd.

Initial release

2012

2000

2010

2014

2019

Current release

5.4, July 2022

1.19, September 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

AGPL version 3, commercial license available

commercial

Open Source

MIT License

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

Clojure

Server operating systems

hosted

Linux

included in appliance

Linux
macOS
Raspberry Pi
Windows

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like query language (RQL)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
OLE DB

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

CLI Client
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

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

Users with fine-grained authorization concept

Authorization levels configured per client per database

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.