InfluxDB vs IronDB

Overview

InfluxDB

Stacks1.0K

Followers1.2K

Votes175

IronDB

Stacks1

Followers11

Votes0

GitHub Stars12

Forks4

InfluxDB vs IronDB: What are the differences?

Introduction: InfluxDB and IronDB are both databases designed for time-series data storage and analysis, but they have key differences that set them apart.

1. Data Storage Architecture: InfluxDB uses a traditional database storage model where data is stored in a series of time-stamped measurements, tags, and fields. IronDB, on the other hand, leverages LSM (Log-Structured Merge) tree storage architecture, which offers superior compression and efficiency in storing and accessing time-series data.

2. Performance and Scalability: InfluxDB is optimized for fast writes and queries on time-series data, making it ideal for real-time data processing and analysis. IronDB boasts exceptional performance and scalability due to its efficient storage architecture, enabling it to handle large volumes of time-series data with lower latency and higher throughput.

3. Data Consistency and Durability: InfluxDB ensures data consistency by employing a distributed consensus algorithm to maintain strong consistency across nodes in a cluster. IronDB guarantees data durability by using durable write-ahead logs and checkpoints, minimizing the risk of data loss in case of failures.

4. Query Language and Data Processing: InfluxDB supports its query language, InfluxQL, tailored for time-series data analysis and manipulation. IronDB integrates seamlessly with popular query languages such as SQL, allowing users to leverage their existing SQL skills for analyzing time-series data more efficiently.

5. Storage Optimization and Compression: InfluxDB offers basic data compression techniques to optimize storage efficiency, but it may not be as effective as IronDB's advanced compression algorithms, which significantly reduce the storage footprint and enhance data retrieval performance.

6. High Availability and Fault Tolerance: While InfluxDB provides options for high availability setups with data replication and clustering, IronDB excels in fault tolerance by leveraging its storage architecture to maintain data integrity and availability even in the face of hardware failures or network issues.

In Summary, InfluxDB and IronDB differ in their data storage architecture, performance and scalability, data consistency and durability, query language and data processing, storage optimization and compression, as well as high availability and fault tolerance capabilities.

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Advice on InfluxDB, IronDB

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

pionell

Sep 16, 2020

Needs adviceon

MariaDB

I have a lot of data that's currently sitting in a MariaDB database, a lot of tables that weigh 200gb with indexes. Most of the large tables have a date column which is always filtered, but there are usually 4-6 additional columns that are filtered and used for statistics. I'm trying to figure out the best tool for storing and analyzing large amounts of data. Preferably self-hosted or a cheap solution. The current problem I'm running into is speed. Even with pretty good indexes, if I'm trying to load a large dataset, it's pretty slow.

159k views159k

Comments

Detailed Comparison

InfluxDB	IronDB
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.	IronDB is the best way to store persistent key-value data in the browser. Data saved to IronDB is redundantly stored in Cookies, IndexedDB, LocalStorage, and SessionStorage, and relentlessly self heals if any data therein is deleted or corrupted.
Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer	-
Statistics
GitHub Stars -	GitHub Stars 12
GitHub Forks -	GitHub Forks 4
Stacks 1.0K	Stacks 1
Followers 1.2K	Followers 11
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

What are some alternatives to InfluxDB, IronDB?

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 IronDB: What are the differences?

Introduction: InfluxDB and IronDB are both databases designed for time-series data storage and analysis, but they have key differences that set them apart.

InfluxDB vs IronDB

Overview