DBMS > Bangdb vs. Citus vs. Hazelcast vs. XTDB

System Properties Comparison Bangdb vs. Citus vs. Hazelcast vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A widely adopted in-memory data grid

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

Document store

Secondary database models

Spatial DBMS

Document store

JSON support with IMDG 3.12

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

bangdb.com

www.citusdata.com

hazelcast.com

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

Technical documentation

docs.bangdb.com

docs.citusdata.com

hazelcast.org/imdg/docs

www.xtdb.com/docs

Developer

Sachin Sinha, BangDB

Hazelcast

Juxt Ltd.

Initial release

2012

2010

2008

2019

Current release

BangDB 2.0, October 2021

8.1, December 2018

5.3.6, November 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2; commercial licenses available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

Clojure

Server operating systems

Linux

All OS with a Java VM

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

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.

yes

specific XML type available, but no XML query functionality

yes

the object must implement a serialization strategy

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

standard, with numerous extensions

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Java
Python

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Event Listeners, Executor Services

Triggers

yes, Notifications (with Streaming only)

yes

Events

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

other methods possible by using 3rd party extensions

yes

Replicated Map

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

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

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Role-based access control

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