DBMS > Apache Druid vs. EsgynDB vs. Immudb vs. Netezza

System Properties Comparison Apache Druid vs. EsgynDB vs. Immudb vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

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

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

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.25
Rank	#307	Overall
	#43	Key-value stores

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Website

druid.apache.org

www.esgyn.cn

github.com/codenotary/immudb
immudb.io

www.ibm.com/products/netezza

Technical documentation

druid.apache.org/docs/latest/design

docs.immudb.io

Developer

Apache Software Foundation and contributors

Esgyn

Codenotary

IBM

Initial release

2012

2015

2020

2000

Current release

29.0.1, April 2024

1.2.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2.0

commercial

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
Unix

Linux

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

included in appliance

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

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

yes

SQL-like syntax

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC
OLE DB

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
Go
Java
JavaScript (Node.js)
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication between multi datacenters

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

In-memory capabilities

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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More resources

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