DBMS > BigObject vs. Cachelot.io vs. Elasticsearch vs. EXASOL

System Properties Comparison BigObject vs. Cachelot.io vs. Elasticsearch vs. EXASOL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

In-memory caching system

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.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Website

bigobject.io

cachelot.io

www.elastic.co/elasticsearch

www.exasol.com

Technical documentation

docs.bigobject.io

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

www.exasol.com/resources

Developer

BigObject, Inc.

Elastic

Exasol

Initial release

2015

2010

2000

Current release

8.6, January 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Simplified BSD License

Open Source

Elastic License

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

yes

schema-free

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

yes

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Memcached protocol

Java API
RESTful HTTP/JSON API

.Net
JDBC
ODBC
WebSocket

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

Java
Lua
Python
R

Server-side scripts

Stored procedures

Lua

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

none

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

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Memcached and Redis integration

yes

User concepts

Access control

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Elastic Reports 8x Speed and 32x Efficiency Gains for Elasticsearch and Lucene Vector Database
26 April 2024, Business Wire

8 Powerful Alternatives to Elasticsearch
25 April 2024, Yahoo Finance

Splunk vs Elasticsearch | A Comparison and How to Choose
12 January 2024, SentinelOne

Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview)
26 March 2024, insider.govtech.com

ElasticSearch Goes Deep on OpenTelemetry with eBPF Donation
13 March 2024, The New Stack

provided by Google News

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
20 March 2024, Business Wire

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
22 February 2024, AiThority

Exasol Reimagines In-Memory Analytics with Major Database Update
30 May 2023, Datanami

provided by Google News

Share this page