DBMS > Amazon DynamoDB vs. CockroachDB vs. Drizzle vs. GeoSpock

System Properties Comparison Amazon DynamoDB vs. CockroachDB vs. Drizzle vs. GeoSpock

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Spatial and temporal data processing engine for extreme data scale

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

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	5.73
Rank	#58	Overall
	#34	Relational DBMS

Website

aws.amazon.com/dynamodb

www.cockroachlabs.com

geospock.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.cockroachlabs.com/docs

Developer

Amazon

Cockroach Labs

Drizzle project, originally started by Brian Aker

GeoSpock

Initial release

2012

2015

2008

Current release

24.1.0, May 2024

7.2.4, September 2012

2.0, September 2019

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

GNU GPL

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

C++

Java, Javascript

Server operating systems

hosted

Linux
macOS
Windows

FreeBSD
Linux
OS X

hosted

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.

Secondary indexes

yes

temporal, categorical

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

with proprietary extensions

ANSI SQL for query only (using Presto)

APIs and other access methods

RESTful HTTP API

JDBC

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
C++
Java
PHP

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

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

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

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)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per table

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