DBMS > Apache Druid vs. Dgraph vs. Hive vs. Yanza

System Properties Comparison Apache Druid vs. Dgraph vs. Hive vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza 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

Distributed and scalable native Graph DBMS

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS

Relational DBMS

Time Series DBMS

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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Website

druid.apache.org

dgraph.io

hive.apache.org

yanza.com

Technical documentation

druid.apache.org/docs/latest/design

dgraph.io/docs

cwiki.apache.org/confluence/display/Hive/Home

Developer

Apache Software Foundation and contributors

Dgraph Labs, Inc.

Apache Software Foundation

initially developed by Facebook

Yanza

Initial release

2012

2016

2012

2015

Current release

29.0.1, April 2024

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

All OS with a Java VM

Windows

Data scheme

yes

schema-less columns are supported

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

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

APIs and other access methods

JDBC
RESTful HTTP/JSON API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
Thrift

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Synchronous replication via Raft

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

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.

User concepts

Access control

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

Planned for future releases

Access rights for users, groups and roles

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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