DBMS > Elasticsearch vs. Google BigQuery vs. Hive vs. IBM Db2 Event Store vs. Percona Server for MongoDB

System Properties Comparison Elasticsearch vs. Google BigQuery vs. Hive vs. IBM Db2 Event Store vs. Percona Server for MongoDB

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Distributed Event Store optimized for Internet of Things use cases

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Search engine

Relational DBMS

Event Store
Time Series DBMS

Document store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.55
Rank	#253	Overall
	#39	Document stores

Website

www.elastic.co/elasticsearch

cloud.google.com/bigquery

hive.apache.org

www.ibm.com/products/db2-event-store

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

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

cloud.google.com/bigquery/docs

cwiki.apache.org/confluence/display/Hive/Home

www.ibm.com/docs/en/db2-event-store

docs.percona.com/percona-distribution-for-mongodb

Developer

Elastic

Google

Apache Software Foundation

initially developed by Facebook

IBM

Percona

Initial release

2010

2012

2017

2015

Current release

8.6, January 2023

3.1.3, April 2022

2.0

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

Apache Version 2

commercial

free developer edition available

Open Source

GPL Version 2

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 and C++

C++

Server operating systems

All OS with a Java VM

hosted

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

Linux

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

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 query language

yes

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

APIs and other access methods

Java API
RESTful HTTP/JSON API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

yes

JavaScript

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Active-active shard replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

query execution via MapReduce

yes

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

Eventual Consistency
Immediate 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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

via In-Memory Engine

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Access rights for users and roles

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.