DBMS > Amazon CloudSearch vs. Apache Druid vs. Google Cloud Datastore vs. GreptimeDB vs. Microsoft SQL Server

System Properties Comparison Amazon CloudSearch vs. Apache Druid vs. Google Cloud Datastore vs. GreptimeDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Microsofts flagship relational DBMS

Primary database model

Search engine

Relational DBMS
Time Series DBMS

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/cloudsearch

druid.apache.org

cloud.google.com/datastore

greptime.com

www.microsoft.com/en-us/sql-server

Technical documentation

docs.aws.amazon.com/cloudsearch

druid.apache.org/docs/latest/design

cloud.google.com/datastore/docs

docs.greptime.com

learn.microsoft.com/en-US/sql/sql-server

Developer

Amazon

Apache Software Foundation and contributors

Google

Greptime Inc.

Microsoft

Initial release

2012

2008

2022

1989

Current release

29.0.1, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Rust

C++

Server operating systems

hosted

Linux
OS X
Unix

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
Windows

Data scheme

yes

schema-less columns are supported

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL for querying

SQL-like query language (GQL)

yes

APIs and other access methods

HTTP API

JDBC
RESTful HTTP/JSON API

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

gRPC
HTTP API
JDBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C++
Erlang
Go
Java
JavaScript

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

Server-side scripts

Stored procedures

using Google App Engine

Python

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

manual/auto, time-based

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes, via HDFS, S3 or other storage engines

Multi-source replication using Paxos

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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