DBMS > Apache Drill vs. GridGain vs. Lovefield vs. SiteWhere

System Properties Comparison Apache Drill vs. GridGain vs. Lovefield vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

Embeddable relational database for web apps written in pure JavaScript

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series 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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

drill.apache.org

www.gridgain.com

google.github.io/lovefield

github.com/sitewhere/sitewhere

Technical documentation

drill.apache.org/docs

www.gridgain.com/docs/index.html

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

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation

GridGain Systems, Inc.

Google

SiteWhere

Initial release

2012

2007

2014

2010

Current release

1.20.3, January 2023

GridGain 8.5.1

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

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

Java, C++, .Net

JavaScript

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

schema-free

yes

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

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST

Supported programming languages

C++

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Security Hooks for custom implementations

Users with fine-grained authorization concept

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More resources

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