DBMS > Amazon DynamoDB vs. Trafodion vs. Vitess vs. XTDB

System Properties Comparison Amazon DynamoDB vs. Trafodion vs. Vitess vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Transactional SQL-on-Hadoop DBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Secondary database models

Document store
Spatial 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	0.88
Rank	#203	Overall
	#95	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/dynamodb

trafodion.apache.org

vitess.io

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

Technical documentation

docs.aws.amazon.com/dynamodb

trafodion.apache.org/documentation.html

vitess.io/docs

www.xtdb.com/docs

Developer

Amazon

Apache Software Foundation, originally developed by HP

The Linux Foundation, PlanetScale

Juxt Ltd.

Initial release

2012

2014

2013

2019

Current release

2.3.0, February 2019

15.0.2, December 2022

1.19, September 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

Open Source

Apache Version 2.0, commercial licenses available

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

C++, Java

Clojure

Server operating systems

hosted

Linux

Docker
Linux
macOS

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

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HBase

Multi-source replication
Source-replica replication

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

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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 at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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.