DBMS > Apache Drill vs. Google BigQuery vs. Informix vs. ToroDB

System Properties Comparison Apache Drill vs. Google BigQuery vs. Informix vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Large scale data warehouse service with append-only tables

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Relational DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Document store

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Website

drill.apache.org

cloud.google.com/bigquery

www.ibm.com/products/informix

github.com/torodb/server

Technical documentation

drill.apache.org/docs

cloud.google.com/bigquery/docs

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

Developer

Apache Software Foundation

Google

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

8Kdata

Initial release

2012

2010

1984

2016

Current release

1.20.3, January 2023

14.10.FC5, November 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

Open Source

AGPL-V3

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, C++ and Java

Java

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

string, integer, double, boolean, date, object_id

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying 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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authentication, authorization, and auditing controls

Access rights for users and roles

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