DBMS > Elasticsearch vs. Google BigQuery vs. Quasardb vs. SAP IQ

System Properties Comparison Elasticsearch vs. Google BigQuery vs. Quasardb vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Large scale data warehouse service with append-only tables

Distributed, high-performance timeseries database

Columnar RDBMS optimized for Big Data analytics

Primary database model

column-oriented

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

www.elastic.co/elasticsearch

cloud.google.com/bigquery

quasar.ai

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

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

cloud.google.com/bigquery/docs

doc.quasar.ai/master

help.sap.com/docs/SAP_IQ

Developer

Elastic

Google

quasardb

SAP, formerly Sybase

Initial release

2010

2009

1994

Current release

8.6, January 2023

3.14.1, January 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Elastic License

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++

Server operating systems

All OS with a Java VM

hosted

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

RESTful HTTP/JSON API

HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with selectable replication factor

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

by using LevelDB

yes

In-memory capabilities

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

Memcached and Redis integration

yes

Transient mode

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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