DBMS > Amazon DynamoDB vs. Hive vs. RavenDB vs. Teradata

System Properties Comparison Amazon DynamoDB vs. Hive vs. RavenDB vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Open Source Operational and Transactional Enterprise NoSQL Document Database

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series 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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

aws.amazon.com/dynamodb

hive.apache.org

ravendb.net

www.teradata.com

Technical documentation

docs.aws.amazon.com/dynamodb

cwiki.apache.org/confluence/display/Hive/Home

ravendb.net/docs

docs.teradata.com

Developer

Amazon

Apache Software Foundation

initially developed by Facebook

Hibernating Rhinos

Teradata

Initial release

2012

2010

1984

Current release

3.1.3, April 2022

5.4, July 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

AGPL version 3, commercial license available

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

Server operating systems

hosted

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

hosted
Linux

Data scheme

schema-free

yes

schema-free

yes

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (RQL)

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

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, Cluster-wide transaction available

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)

Access rights for users, groups and roles

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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