DBMS > Apache Drill vs. Apache Druid vs. GridGain vs. HEAVY.AI vs. Snowflake

System Properties Comparison Apache Drill vs. Apache Druid vs. GridGain vs. HEAVY.AI vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

GridGain is an in-memory computing platform, built on Apache Ignite

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

drill.apache.org

druid.apache.org

www.gridgain.com

github.com/heavyai/heavydb
www.heavy.ai

www.snowflake.com

Technical documentation

drill.apache.org/docs

druid.apache.org/docs/latest/design

www.gridgain.com/docs/index.html

docs.heavy.ai

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache Software Foundation and contributors

GridGain Systems, Inc.

HEAVY.AI, Inc.

Snowflake Computing Inc.

Initial release

2012

2007

2016

2014

Current release

1.20.3, January 2023

29.0.1, April 2024

GridGain 8.5.1

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache license v2

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++, .Net

C++ and CUDA

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

schema-free

yes

schema-less columns are supported

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL for querying

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Supported programming languages

C++

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes (replicated cache)

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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