DBMS > Amazon DynamoDB vs. Apache Impala vs. Couchbase vs. Postgres-XL

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. Couchbase vs. Postgres-XL

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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

Analytic DBMS for Hadoop

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

aws.amazon.com/dynamodb

impala.apache.org

www.couchbase.com

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/dynamodb

impala.apache.org/impala-docs.html

docs.couchbase.com

www.postgres-xl.org/documentation

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Couchbase, Inc.

Initial release

2012

2013

2011

2014

since 2012, originally named StormDB

Current release

4.1.0, June 2022

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Mozilla public 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++

C, C++, Go and Erlang

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
macOS

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication

including cross data center 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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

MVCC

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

Ephemeral buckets

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

based on Apache Sentry and Kerberos

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

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