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

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

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Editorial information provided by DB-Engines

Name

Description

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

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

A fast-speed and highly-scalable Graph DBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Relational DBMS

Time Series DBMS

Graph DBMS

Graph DBMS
RDF store

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

drill.apache.org

github.com/spotify/heroic

github.com/hugegraph
hugegraph.apache.org

www.stardog.com

Technical documentation

drill.apache.org/docs

spotify.github.io/heroic

hugegraph.apache.org/docs

docs.stardog.com

Developer

Apache Software Foundation

Spotify

Baidu

Stardog-Union

Initial release

2012

2014

2018

2010

Current release

1.20.3, January 2023

0.9

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Unix

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

via Elasticsearch

yes

also supports composite index and range index

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

Java API
RESTful HTTP API
TinkerPop Gremlin

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C++

Groovy
Java
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication in HA-Cluster

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

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

edges in graph

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

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

User concepts

Access control

Depending on the underlying data source

Users, roles and permissions

Access rights for users and roles

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More resources

Recent citations in the news

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

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

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

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

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

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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