DBMS > Apache Drill vs. Datomic vs. Hive vs. Yaacomo

System Properties Comparison Apache Drill vs. Datomic vs. Hive vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Relational DBMS

Relational 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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

drill.apache.org

www.datomic.com

hive.apache.org

yaacomo.com

Technical documentation

drill.apache.org/docs

docs.datomic.com

cwiki.apache.org/confluence/display/Hive/Home

Developer

Apache Software Foundation

Cognitect

Apache Software Foundation

initially developed by Facebook

Q2WEB GmbH

Initial release

2012

2009

Current release

1.20.3, January 2023

1.0.6735, June 2023

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Android
Linux
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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

C++

Clojure
Java

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

yes

user defined functions and integration of map-reduce

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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