DBMS > Apache Drill vs. EDB Postgres vs. Lovefield vs. Riak TS vs. SiteWhere

System Properties Comparison Apache Drill vs. EDB Postgres vs. Lovefield vs. Riak TS vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Embeddable relational database for web apps written in pure JavaScript

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

drill.apache.org

www.enterprisedb.com

google.github.io/lovefield

github.com/sitewhere/sitewhere

Technical documentation

drill.apache.org/docs

www.enterprisedb.com/docs

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

www.tiot.jp/riak-docs/riak/ts/latest

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation

EnterpriseDB

Google

Open Source, formerly Basho Technologies

SiteWhere

Initial release

2012

2005

2014

2015

2010

Current release

1.20.3, January 2023

14, December 2021

2.1.12, February 2017

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

BSD for PostgreSQL-components

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Erlang

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

predefined scheme

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

yes, limited

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

C++

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

Triggers

yes

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

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

yes

In-memory capabilities

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

Depending on the underlying data source

yes

using MemoryDB

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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More resources

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