DBMS > Apache Drill vs. H2 vs. Lovefield vs. Splice Machine

System Properties Comparison Apache Drill vs. H2 vs. Lovefield vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable relational database for web apps written in pure JavaScript

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

drill.apache.org

www.h2database.com

google.github.io/lovefield

splicemachine.com

Technical documentation

drill.apache.org/docs

www.h2database.com/html/main.html

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

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Thomas Mueller

Google

Splice Machine

Initial release

2012

2005

2014

Current release

1.20.3, January 2023

2.2.220, July 2023

2.1.12, February 2017

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C++

Java

JavaScript

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

yes

Java

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

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

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

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

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

Recent citations in the news

MapR to Speak on Stream Processing Systems, Apache Spark and Drill at Industry Events in January
31 May 2024, Yahoo Movies UK

Analyse Kafka messages with SQL queries using Apache Drill
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Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

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Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

New Splice Machine RDBMS unites OLTP and OLAP
18 November 2015, CIO

How To Axe Db2 But Keep Your Code
10 March 2020, Towards Data Science

Hadoop-based RDBMS Now Available from Splice
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