DBMS > Apache Drill vs. EsgynDB vs. LevelDB vs. Riak TS

System Properties Comparison Apache Drill vs. EsgynDB vs. LevelDB vs. Riak TS

Please select another system to include it in the comparison.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

drill.apache.org

www.esgyn.cn

github.com/google/leveldb

Technical documentation

drill.apache.org/docs

github.com/google/leveldb/blob/main/doc/index.md

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Esgyn

Google

Open Source, formerly Basho Technologies

Initial release

2012

2015

2011

2015

Current release

1.20.3, January 2023

1.23, February 2021

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

BSD

Open Source

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

C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux

Illumos
Linux
OS X
Windows

Linux
OS X

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

restricted

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

yes, limited

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

C++

All languages supporting JDBC/ODBC/ADO.Net

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

selectable replication factor

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

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

with automatic compression on writes

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

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, businesswire.com

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

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

provided by Google News

Inside the "Fallguys" malware that steals your browsing data and gaming IMs; continued attack on open source software
2 September 2020, Sonatype Blog

Pliops unveils XDP-Rocks for RocksDB
19 October 2022, Blocks & Files

AMD EPYC vs. Intel Xeon Cascadelake With Facebook's RocksDB Database
17 October 2019, Phoronix

RocksDB - Facebook's Database Now Open Source
21 November 2013, iProgrammer

GIFShell - New Attack Method That Allows Attackers to Steal Data Using Microsoft Teams GIFs
9 September 2022, CybersecurityNews

provided by Google News

Is Riak A Good NoSQL Database Option For Enterprises?
1 July 2019, AIM

Best open source databases for IoT applications
26 May 2017, Open Source For You

provided by Google News

Share this page