DBMS > Amazon CloudSearch vs. Apache IoTDB vs. GreptimeDB vs. OrigoDB

System Properties Comparison Amazon CloudSearch vs. Apache IoTDB vs. GreptimeDB vs. OrigoDB

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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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

A fully ACID in-memory object graph database

Primary database model

Search engine

Time Series DBMS

Document store
Object oriented DBMS

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

Score	1.86
Rank	#133	Overall
	#12	Search engines

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Website

aws.amazon.com/cloudsearch

iotdb.apache.org

greptime.com

origodb.com

Technical documentation

docs.aws.amazon.com/cloudsearch

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.greptime.com

origodb.com/docs

Developer

Amazon

Apache Software Foundation

Greptime Inc.

Robert Friberg et al

Initial release

2012

2018

2022

2009

under the name LiveDB

Current release

1.1.0, April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

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

Rust

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

JDBC
Native API

gRPC
HTTP API
JDBC

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C++
Erlang
Go
Java
JavaScript

.Net

Server-side scripts

Stored procedures

yes

Python

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

yes

Simple rights management via user accounts

Role based authorization

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
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Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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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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