DBMS > Apache Druid vs. BigchainDB vs. HyperSQL vs. Postgres-XL

System Properties Comparison Apache Druid vs. BigchainDB vs. HyperSQL vs. Postgres-XL

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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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial 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	0.85
Rank	#208	Overall
	#35	Document stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

bigchaindb.readthedocs.io/en/latest

hsqldb.org/web/hsqlDocsFrame.html

www.postgres-xl.org/documentation

Developer

Apache Software Foundation and contributors

Initial release

2012

2016

2001

2014

since 2012, originally named StormDB

Current release

29.0.1, April 2024

2.7.2, June 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

AGPL v3

Open Source

based on BSD license

Open Source

Mozilla public license

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

Python

Java

Server operating systems

Linux
OS X
Unix

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS

Data scheme

yes

schema-less columns are supported

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

distributed, parallel query execution

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

All languages supporting JDBC/ODBC
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Java, SQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

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More resources

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