DBMS > Apache Drill vs. EsgynDB vs. KairosDB vs. Machbase Neo vs. RDF4J

System Properties Comparison Apache Drill vs. EsgynDB vs. KairosDB vs. Machbase Neo vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed Time Series DBMS based on Cassandra or H2

TimeSeries DBMS for AIoT and BigData

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series 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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

drill.apache.org

www.esgyn.cn

github.com/kairosdb/kairosdb

machbase.com

rdf4j.org

Technical documentation

drill.apache.org/docs

kairosdb.github.io

machbase.com/dbms

rdf4j.org/documentation

Developer

Apache Software Foundation

Esgyn

Machbase

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2015

2013

2004

Current release

1.20.3, January 2023

1.2.2, November 2018

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

free test version available

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++, Java

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

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

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

selectable replication factor

none

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

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

in-memory storage is supported as well

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

volatile and lookup table

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

simple password-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

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

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

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

provided by Google News

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs
24 May 2019, InfoQ.com

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

provided by Google News

Share this page