DBMS > Amazon DynamoDB vs. CockroachDB vs. Hive vs. Ingres

System Properties Comparison Amazon DynamoDB vs. CockroachDB vs. Hive vs. Ingres

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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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

Well established RDBMS

Primary database model

Document store
Key-value store

Relational 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	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Website

aws.amazon.com/dynamodb

www.cockroachlabs.com

hive.apache.org

www.actian.com/databases/ingres

Technical documentation

docs.aws.amazon.com/dynamodb

www.cockroachlabs.com/docs

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

docs.actian.com/ingres

Developer

Amazon

Cockroach Labs

Apache Software Foundation

initially developed by Facebook

Actian Corporation

Initial release

2012

2015

2012

1974

originally developed at University Berkely in early 1970s

Current release

24.1.0, May 2024

3.1.3, April 2022

11.2, May 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0, commercial license available

Open Source

Apache 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

Server operating systems

hosted

Linux
macOS
Windows

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

dynamic schema

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP API

JDBC

JDBC
ODBC
Thrift

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

selectable replication factor

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

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

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

MVCC

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.

User concepts

Access control

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

Role-based access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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