DBMS > Elasticsearch vs. Firebolt vs. Google BigQuery vs. Memcached vs. Rockset

System Properties Comparison Elasticsearch vs. Firebolt vs. Google BigQuery vs. Memcached vs. Rockset

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Large scale data warehouse service with append-only tables

In-memory key-value store, originally intended for caching

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Relational DBMS
Search engine

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

www.elastic.co/elasticsearch

www.firebolt.io

cloud.google.com/bigquery

www.memcached.org

rockset.com

Technical documentation

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

docs.firebolt.io

cloud.google.com/bigquery/docs

github.com/memcached/memcached/wiki

docs.rockset.com

Developer

Elastic

Firebolt Analytics Inc.

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Rockset

Initial release

2010

2020

2010

2003

2019

Current release

8.6, January 2023

1.6.27, May 2024

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

BSD license

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

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic 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.

ingestion from XML files supported

Secondary indexes

yes

All search fields are automatically indexed

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

Java API
RESTful HTTP/JSON API

.Net
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

Proprietary protocol

HTTP REST

Supported programming languages

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

Go
JavaScript (Node.js)
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

none

Repcached, a Memcached patch, provides this functionallity

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

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.

Memcached and Redis integration

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and organizations can be defined via Rockset console

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.