DBMS > Elasticsearch vs. Google Cloud Datastore vs. MySQL vs. NSDb vs. StarRocks

System Properties Comparison Elasticsearch vs. Google Cloud Datastore vs. MySQL vs. NSDb vs. StarRocks

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Widely used open source RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Search engine

Document store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

www.elastic.co/elasticsearch

cloud.google.com/datastore

www.mysql.com

nsdb.io

www.starrocks.io

Technical documentation

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

cloud.google.com/datastore/docs

dev.mysql.com/doc

nsdb.io/Architecture

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Elastic

Google

Oracle

since 2010, originally MySQL AB, then Sun

The Linux Foundation

since Feb 2023

Initial release

2010

2008

1995

2017

2020

Current release

8.6, January 2023

8.4.0, April 2024

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Java, Scala

C++, Java

Server operating systems

All OS with a Java VM

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Linux

Data scheme

schema-free

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

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

yes: int, bigint, decimal, string

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (GQL)

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
HTTP REST
WebSocket

JDBC
MySQL protocol

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
Scala

Java

Server-side scripts

Stored procedures

yes

using Google App Engine

yes

proprietary syntax

user defined functions

Triggers

yes

by using the 'percolation' feature

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

using Google Cloud Dataflow

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 or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

Role based access control and fine grained access rights

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