DBMS > Apache Drill vs. Bangdb vs. Heroic vs. HugeGraph

System Properties Comparison Apache Drill vs. Bangdb vs. Heroic vs. HugeGraph

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A fast-speed and highly-scalable Graph DBMS

Primary database model

Document store
Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Website

drill.apache.org

bangdb.com

github.com/spotify/heroic

github.com/hugegraph
hugegraph.apache.org

Technical documentation

drill.apache.org/docs

docs.bangdb.com

spotify.github.io/heroic

hugegraph.apache.org/docs

Developer

Apache Software Foundation

Sachin Sinha, BangDB

Spotify

Baidu

Initial release

2012

2014

2018

Current release

1.20.3, January 2023

BangDB 2.0, October 2021

0.9

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Unix

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

via Elasticsearch

yes

also supports composite index and range index

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL like support with command line tool

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

C++

C
C#
C++
Java
Python

Groovy
Java
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Depending on the underlying data source

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.

Depending on the underlying data source

yes, run db with in-memory only mode

yes

User concepts

Access control

Depending on the underlying data source

yes (enterprise version only)

Users, roles and permissions

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More resources

Recent citations in the news

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Using Apache Iceberg for Developing Modern Data Tables
3 October 2023, Open Source For You

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

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