DBMS > Amazon DynamoDB vs. BaseX vs. CockroachDB vs. Warp 10 vs. Yaacomo

System Properties Comparison Amazon DynamoDB vs. BaseX vs. CockroachDB vs. Warp 10 vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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.

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/dynamodb

basex.org

www.cockroachlabs.com

www.warp10.io

yaacomo.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.basex.org

www.cockroachlabs.com/docs

www.warp10.io/content/02_Getting_started

Developer

Amazon

BaseX GmbH

Cockroach Labs

SenX

Q2WEB GmbH

Initial release

2012

2007

2015

2009

Current release

10.7, August 2023

24.1.0, May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD license

Open Source

Apache 2.0, commercial license available

Open Source

Apache License 2.0

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
OS X
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

schema-free

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

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

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC

HTTP API
Jupyter
WebSocket

JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

by integration with AWS Lambda

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication using RAFT

selectable replication factor

based on HBase

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

based on HBase

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

multiple readers, single writer

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)

Users with fine-grained authorization concept on 4 levels

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

fine grained access rights according to SQL-standard

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