DBMS > Apache Druid vs. EsgynDB vs. NSDb vs. WakandaDB

System Properties Comparison Apache Druid vs. EsgynDB vs. NSDb vs. WakandaDB

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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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Object oriented DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

nsdb.io/Architecture

wakanda.github.io/doc

Developer

Apache Software Foundation and contributors

Esgyn

Wakanda SAS

Initial release

2012

2015

2017

2012

Current release

29.0.1, April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2.0

Open Source

AGPLv3, extended commercial license available

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

Java, Scala

C++, JavaScript

Server operating systems

Linux
OS X
Unix

Linux

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

Java
Scala

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

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

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

yes

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More resources

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