DBMS > Bangdb vs. Hive vs. Kyligence Enterprise vs. PostGIS

System Properties Comparison Bangdb vs. Hive vs. Kyligence Enterprise vs. PostGIS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

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

A distributed analytics engine for big data, built on top of Apache Kylin

Spatial extension of PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

bangdb.com

hive.apache.org

kyligence.io/kyligence-enterprise

postgis.net

Technical documentation

docs.bangdb.com

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

postgis.net/documentation

Developer

Sachin Sinha, BangDB

Apache Software Foundation

initially developed by Facebook

Kyligence, Inc.

Initial release

2012

2016

2005

Current release

BangDB 2.0, October 2021

3.1.3, April 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2

commercial

Open Source

GPL v2.0

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

C, C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Thrift

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

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

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

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

yes (enterprise version only)

Access rights for users, groups and roles

yes

based on PostgreSQL

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

DB-Engines blog posts

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

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

Elevate Your Career with In-Demand Hadoop Skills in 2024
30 April 2024, Simplilearn

provided by Google News

Kyligence Grows OLAP Business in the Cloud
20 February 2020, Datanami

Kyligence adds ClickHouse OLAP engine to its analytics platform
10 August 2021, VentureBeat

Distributed OLAPer Kyligence accelerates core engine, adds real-time data support – Blocks and Files
10 August 2021, Blocks & Files

How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services
9 November 2022, AWS Blog

Kyligence Doubles Down on Cubes in the Cloud
22 January 2021, Datanami

provided by Google News

Share this page