DBMS > Apache Druid vs. Bangdb vs. XTDB

System Properties Comparison Apache Druid vs. Bangdb vs. XTDB

Please select another system to include it in the comparison.

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

Converged and high performance database for device data, events, time series, document and graph

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Secondary database models

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	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

druid.apache.org

bangdb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

druid.apache.org/docs/latest/design

docs.bangdb.com

www.xtdb.com/docs

Developer

Apache Software Foundation and contributors

Sachin Sinha, BangDB

Juxt Ltd.

Initial release

2012

2019

Current release

29.0.1, April 2024

BangDB 2.0, October 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD 3

Open Source

MIT 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

C, C++

Clojure

Server operating systems

Linux
OS X
Unix

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes, extensible-data-notation format

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL for querying

SQL like support with command line tool

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Java
Python

Clojure
Java

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor, Knob for CAP (enterprise version only)

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

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

yes (enterprise version only)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid | by Zisis Flokas
18 October 2021, Towards Data Science

provided by Google News

Share this page