DBMS > Apache Druid vs. Apache Impala vs. EsgynDB vs. FeatureBase vs. JSqlDb

System Properties Comparison Apache Druid vs. Apache Impala vs. EsgynDB vs. FeatureBase vs. JSqlDb

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Analytic DBMS for Hadoop

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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Document store

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Website

jsqldb.org (offline)

Technical documentation

druid.apache.org/docs/latest/design

impala.apache.org/impala-docs.html

docs.featurebase.com

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

Molecula and Pilosa Open Source Contributors

Konrad von Backstrom

Initial release

2012

2013

2015

2017

2018

Current release

29.0.1, April 2024

4.1.0, June 2022

2022, May 2022

0.8, December 2018

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2

commercial

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

Java

C++

C++, Java

Server operating systems

Linux
OS X
Unix

Linux

Linux
macOS

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

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 for querying

SQL-like DML and DDL statements

yes

SQL queries

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC

gRPC
JDBC
Kafka Connector
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

functions in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

Multi-source replication between multi datacenters

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

using RocksDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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