DBMS > Amazon CloudSearch vs. Databricks vs. DolphinDB vs. EsgynDB

System Properties Comparison Amazon CloudSearch vs. Databricks vs. DolphinDB vs. EsgynDB

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Primary database model

Search engine

Document store
Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.86
Rank	#133	Overall
	#12	Search engines

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.databricks.com

www.dolphindb.com

www.esgyn.cn

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.databricks.com

docs.dolphindb.cn/en/help200/index.html

Developer

Amazon

Databricks

DolphinDB, Inc

Esgyn

Initial release

2012

2013

2018

2015

Current release

v2.00.4, January 2022

License

Commercial or Open Source

commercial

free community version available

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

C++

C++, Java

Server operating systems

hosted

Linux
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

Python
R
Scala

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Multi-source replication between multi datacenters

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

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.

yes

User concepts

Access control

authentication via encrypted signatures

Administrators, Users, Groups

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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More resources

DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

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Recent citations in the news

Transition from Amazon CloudSearch to Amazon OpenSearch Service
25 July 2024, AWS Blog

AWS to discontinue Cloud9, CodeCommit, CloudSearch and several other services
31 July 2024, Neowin

AWS is quietly killing off some services under its new CEO
31 July 2024, The Stack

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month
12 April 2012, AWS Blog

Amazon Takes On Google And Microsoft With CloudSearch
16 April 2012, Forbes

provided by Google News

Leading Tech Talent Creation Expert Launches Databricks Data Engineer Program
19 September 2024, Business Wire

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Inside the Snowflake — Databricks Rivalry, and Why Both Fear Microsoft
14 August 2024, Bloomberg

Introducing Databricks AI/BI: Intelligent Analytics for Real-World Data
12 June 2024, PR Newswire

provided by Google News

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