DBMS > Apache Druid vs. Google BigQuery vs. IBM Db2 warehouse vs. SAP IQ vs. YDB

System Properties Comparison Apache Druid vs. Google BigQuery vs. IBM Db2 warehouse vs. SAP IQ vs. YDB

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Cloud-based data warehousing service

Columnar RDBMS optimized for Big Data analytics

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

column-oriented

Document store
Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

druid.apache.org

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

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

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

druid.apache.org/docs/latest/design

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_IQ

ydb.tech/en/docs

Developer

Apache Software Foundation and contributors

Google

IBM

SAP, formerly Sybase

Yandex

Initial release

2012

2010

2014

1994

2019

Current release

29.0.1, April 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

Flexible Schema (defined schema, partial schema, schema free)

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

SQL

Support of SQL

SQL for querying

yes

SQL-like query language (YQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL, SQL PL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

SAP/Sybase Replication Server

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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