InfluxDB vs OrbitDB

Overview

InfluxDB

Stacks1.0K

Followers1.2K

Votes175

OrbitDB

Stacks10

Followers60

Votes0

InfluxDB vs OrbitDB: What are the differences?

InfluxDB and OrbitDB are both popular databases, but they are designed to serve different purposes. InfluxDB is a time-series database that is optimized for handling high volumes of timestamped data efficiently. On the other hand, OrbitDB is a distributed peer-to-peer database that uses IPFS for data storage and synchronization. Here are the key differences between InfluxDB and OrbitDB:

Data Model: InfluxDB uses a tabular data structure with rows and columns, which is suitable for time-series data storage and analysis. OrbitDB, on the other hand, employs a key-value data model that allows users to store and retrieve data in a decentralized manner.
Consistency: InfluxDB offers strong consistency guarantees, ensuring that all nodes in the database cluster have the same view of the data at any given time. In contrast, OrbitDB provides eventual consistency, meaning that data changes will eventually propagate to all nodes but may not be immediately visible everywhere.
Query Language: InfluxDB utilizes an SQL-like query language called InfluxQL, which is specifically optimized for querying time-series data. OrbitDB does not have a query language built-in, and users typically interact with the database using the IPFS API.
Network Architecture: InfluxDB typically operates as a centralized database, with a single master node coordinating data replication and storage. OrbitDB, on the other hand, is designed to be fully decentralized, with no single point of control or failure.
Security Model: InfluxDB offers various authentication and authorization mechanisms to control access to data and resources within the database. OrbitDB relies on IPFS for data encryption and peer authentication, leveraging the security features provided by the underlying protocol.
Use Cases: InfluxDB is well-suited for applications that require real-time monitoring, analytics, and visualization of time-series data, such as IoT sensor data or application performance metrics. OrbitDB, on the other hand, is ideal for building decentralized applications, collaborative tools, and other use cases where data sharing and synchronization between peers are essential.

In Summary, the key differences between InfluxDB and OrbitDB lie in their data models, consistency guarantees, query languages, network architectures, security models, and use cases.

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Advice on InfluxDB, OrbitDB

Anonymous

Apr 21, 2020

Needs advice

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

381k views381k

Comments

Benoit

Principal Engineer at Sqreen

Sep 21, 2019

Decided

I chose TimescaleDB because to be the backend system of our production monitoring system. We needed to be able to keep track of multiple high cardinality dimensions.

The drawbacks of this decision are our monitoring system is a bit more ad hoc than it used to (New Relic Insights)

We are combining this with Grafana for display and Telegraf for data collection

155k views155k

Comments

Detailed Comparison

InfluxDB	OrbitDB
InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.	It is a serverless, distributed, peer-to-peer database. It uses IPFS as its data storage and IPFS Pubsub to automatically sync databases with peers. It’s an eventually consistent database that uses CRDTs for conflict-free database merges making it an excellent choice for decentralized apps (dApps), blockchain applications and offline-first web applications.
Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer	Peer-to-Peer Database; Serverless; Automatically sync databases with peers
Statistics
Stacks 1.0K	Stacks 10
Followers 1.2K	Followers 60
Votes 175	Votes 0
Pros & Cons
Pros 59 Time-series data analysis 30 Easy setup, no dependencies 24 Fast, scalable & open source 21 Open source 20 Real-time analytics Cons 4 Instability 1 Proprietary query language 1 HA or Clustering is only in paid version	No community feedback yet
Integrations
No integrations available	Node.js

What are some alternatives to InfluxDB, OrbitDB?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

InfluxDB vs OrbitDB: What are the differences?

Data Model: InfluxDB uses a tabular data structure with rows and columns, which is suitable for time-series data storage and analysis. OrbitDB, on the other hand, employs a key-value data model that allows users to store and retrieve data in a decentralized manner.
Consistency: InfluxDB offers strong consistency guarantees, ensuring that all nodes in the database cluster have the same view of the data at any given time. In contrast, OrbitDB provides eventual consistency, meaning that data changes will eventually propagate to all nodes but may not be immediately visible everywhere.
Query Language: InfluxDB utilizes an SQL-like query language called InfluxQL, which is specifically optimized for querying time-series data. OrbitDB does not have a query language built-in, and users typically interact with the database using the IPFS API.
Network Architecture: InfluxDB typically operates as a centralized database, with a single master node coordinating data replication and storage. OrbitDB, on the other hand, is designed to be fully decentralized, with no single point of control or failure.
Security Model: InfluxDB offers various authentication and authorization mechanisms to control access to data and resources within the database. OrbitDB relies on IPFS for data encryption and peer authentication, leveraging the security features provided by the underlying protocol.
Use Cases: InfluxDB is well-suited for applications that require real-time monitoring, analytics, and visualization of time-series data, such as IoT sensor data or application performance metrics. OrbitDB, on the other hand, is ideal for building decentralized applications, collaborative tools, and other use cases where data sharing and synchronization between peers are essential.

In Summary, the key differences between InfluxDB and OrbitDB lie in their data models, consistency guarantees, query languages, network architectures, security models, and use cases.

InfluxDB vs OrbitDB

Overview