DBMS > Apache Druid vs. Google BigQuery vs. SAP IQ vs. Solr

System Properties Comparison Apache Druid vs. Google BigQuery vs. SAP IQ vs. Solr

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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

Columnar RDBMS optimized for Big Data analytics

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

column-oriented

Search engine

Secondary database models

Spatial DBMS

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

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

druid.apache.org

cloud.google.com/bigquery

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

solr.apache.org

Technical documentation

druid.apache.org/docs/latest/design

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_IQ

solr.apache.org/resources.html

Developer

Apache Software Foundation and contributors

Google

SAP, formerly Sybase

Apache Software Foundation

Initial release

2012

2010

1994

2006

Current release

29.0.1, April 2024

16.1 SPS04, April 2019

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2

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

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-less columns are supported

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

Solr Parallel SQL Interface

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

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

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

optimistic locking

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

yes

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