DBMS > Elasticsearch vs. EXASOL vs. Google BigQuery vs. OrigoDB

System Properties Comparison Elasticsearch vs. EXASOL vs. Google BigQuery vs. OrigoDB

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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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

A fully ACID in-memory object graph database

Primary database model

Search engine

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.elastic.co/elasticsearch

www.exasol.com

cloud.google.com/bigquery

origodb.com

Technical documentation

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

www.exasol.com/resources

cloud.google.com/bigquery/docs

origodb.com/docs

Developer

Elastic

Exasol

Google

Robert Friberg et al

Initial release

2010

2000

2010

2009

under the name LiveDB

Current release

8.6, January 2023

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

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

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

Supported programming languages

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

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

by using the 'percolation' feature

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

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

depending on model

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

Role based authorization

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