DBMS > Apache Drill vs. HBase vs. Sadas Engine vs. Stardog

System Properties Comparison Apache Drill vs. HBase vs. Sadas Engine vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Relational DBMS

Wide column store

Relational DBMS

Graph DBMS
RDF store

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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

drill.apache.org/docs

hbase.apache.org/book.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.stardog.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

SADAS s.r.l.

Stardog-Union

Initial release

2012

2008

2006

2010

Current release

1.20.3, January 2023

2.3.4, January 2021

8.0

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

free trial version available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

AIX
Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
Proprietary protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C++

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Depending on the underlying data source

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

Access rights for users and roles

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More resources

DB-Engines blog posts

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13 May 2013, Paul Andlinger

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