DBMS > Amazon DynamoDB vs. Datomic vs. Lovefield vs. Postgres-XL vs. VoltDB

System Properties Comparison Amazon DynamoDB vs. Datomic vs. Lovefield vs. Postgres-XL vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable relational database for web apps written in pure JavaScript

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

aws.amazon.com/dynamodb

www.datomic.com

google.github.io/lovefield

www.postgres-xl.org

www.voltdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.datomic.com

github.com/google/lovefield/blob/master/docs/spec_index.md

www.postgres-xl.org/documentation

docs.voltdb.com

Developer

Amazon

Cognitect

Google

VoltDB Inc.

Initial release

2012

2014

since 2012, originally named StormDB

2010

Current release

1.0.6735, June 2023

2.1.12, February 2017

10 R1, October 2018

11.3, April 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

limited edition free

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, Clojure

JavaScript

Java, C++

Server operating systems

hosted

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Linux
OS X

for development

Data scheme

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 query language

via JavaScript builder pattern

yes

distributed, parallel query execution

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java

JavaScript

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Java

Triggers

yes

by integration with AWS Lambda

By using transaction functions

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

none

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

FOREIGN KEY constraints are not supported

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

using MemoryDB

User concepts

Access control

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

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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