DBMS > Apache Druid vs. TDSQL for MySQL vs. WakandaDB vs. Warp 10

System Properties Comparison Apache Druid vs. TDSQL for MySQL vs. WakandaDB vs. Warp 10

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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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Object oriented DBMS

Time Series DBMS

Secondary database models

Document store
Spatial 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	0.85
Rank	#205	Overall
	#95	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

druid.apache.org

www.tencentcloud.com/products/dcdb

wakanda.github.io

www.warp10.io

Technical documentation

druid.apache.org/docs/latest/design

www.tencentcloud.com/document/product/1042

wakanda.github.io/doc

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation and contributors

Tencent

Wakanda SAS

SenX

Initial release

2012

2013

2012

2015

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

AGPLv3, extended commercial license available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, JavaScript

Java

Server operating systems

Linux
OS X
Unix

hosted

Linux
OS X
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

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Java
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

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.

yes

User concepts

Access control

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

Users with fine-grained authorization concept

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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