DBMS > Apache Drill vs. Graph Engine vs. Hive vs. SWC-DB

System Properties Comparison Apache Drill vs. Graph Engine vs. Hive vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Wide column store

Secondary database models

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	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

drill.apache.org

www.graphengine.io

hive.apache.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

drill.apache.org/docs

www.graphengine.io/docs/manual

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

Developer

Apache Software Foundation

Microsoft

Apache Software Foundation

initially developed by Facebook

Alex Kashirin

Initial release

2012

2010

2012

2020

Current release

1.20.3, January 2023

3.1.3, April 2022

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

Apache Version 2

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

.NET and C

Java

C++

Server operating systems

Linux
OS X
Windows

.NET

All OS with a Java VM

Linux

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
Thrift

Proprietary protocol
Thrift

Supported programming languages

C++

C#
C++
F#
Visual Basic

C++
Java
PHP
Python

C++

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

User concepts

Access control

Depending on the underlying data source

Access rights for users, groups and roles

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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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