DBMS > Amazon Neptune vs. Apache IoTDB vs. Databend vs. OpenSearch vs. Tkrzw

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. Databend vs. OpenSearch vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the 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, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Secondary database models

Vector DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

aws.amazon.com/neptune

iotdb.apache.org

github.com/datafuselabs/databend
www.databend.com

github.com/opensearch-project
opensearch.org

dbmx.net/tkrzw

Technical documentation

aws.amazon.com/neptune/developer-resources

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

docs.databend.com

opensearch.org/docs/latest

Developer

Amazon

Apache Software Foundation

Databend Labs

Amazon Web Services

Mikio Hirabayashi

Initial release

2017

2018

2021

2020

Current release

1.1.0, April 2023

1.0.59, April 2023

2.5.0, January 2023

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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.

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Implementation language

Java

Rust

Java

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

hosted
Linux
macOS

All OS with a Java VM

Linux
macOS

Data scheme

schema-free

yes

schema-free

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

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

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
Native API

CLI Client
JDBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

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

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

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

none

yes

none

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

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

Users with fine-grained authorization concept, user roles

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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