DBMS > Apache Drill vs. EsgynDB vs. GridGain vs. SAP IQ vs. Snowflake

System Properties Comparison Apache Drill vs. EsgynDB vs. GridGain vs. SAP IQ vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

column-oriented

Relational 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	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

drill.apache.org

www.esgyn.cn

www.gridgain.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

Technical documentation

drill.apache.org/docs

www.gridgain.com/docs/index.html

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Esgyn

GridGain Systems, Inc.

SAP, formerly Sybase

Snowflake Computing Inc.

Initial release

2012

2015

2007

1994

2014

Current release

1.20.3, January 2023

GridGain 8.5.1

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Java, C++, .Net

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

schema-free

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

yes

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C++

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

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

yes

user defined functions

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes (replicated cache)

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Hadoop integration

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

fine grained access rights according to SQL-standard

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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