DBMS > Apache Drill vs. Datomic vs. H2 vs. Heroic

System Properties Comparison Apache Drill vs. Datomic vs. H2 vs. Heroic

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Editorial information provided by DB-Engines

Name

Description

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

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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

drill.apache.org

www.datomic.com

www.h2database.com

github.com/spotify/heroic

Technical documentation

drill.apache.org/docs

docs.datomic.com

www.h2database.com/html/main.html

spotify.github.io/heroic

Developer

Apache Software Foundation

Cognitect

Thomas Mueller

Spotify

Initial release

2012

2005

2014

Current release

1.20.3, January 2023

1.0.6735, June 2023

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

Open Source

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

Open Source

Apache 2.0

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, Clojure

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

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

via Elasticsearch

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

C++

Clojure
Java

Java

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

Java Stored Procedures and User-Defined Functions

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

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

yes

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

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

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

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

recommended only for testing and development

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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