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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Heroic vs InfluxDB

Heroic vs InfluxDB

OverviewDecisionsComparisonAlternatives

Overview

InfluxDB
InfluxDB
Stacks1.0K
Followers1.2K
Votes175
Heroic
Heroic
Stacks5
Followers25
Votes0
GitHub Stars846
Forks106

Heroic vs InfluxDB: What are the differences?

Developers describe Heroic as "A scalable time series database based on Cassandra and Elasticsearch, by Spotify". Heroic is Spotify's in-house time series database. It was built to address the challenges Spotify was facing with near real-time data collection and presentation at scale. On the other hand, InfluxDB is detailed as "An open-source distributed time series database with no external dependencies". 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..

Heroic and InfluxDB can be primarily classified as "Databases" tools.

Some of the features offered by Heroic are:

  • heroic-core contains the com.spotify.heroic.HeroicCore class which is the central building block for setting up a Heroic instance.
  • heroic-elasticsearch-utils is a collection of utilities for interacting with Elasticsearch. This is separate since we have more than one backend that needs to talk with elasticsearch.
  • heroic-parser provides an Antlr4 implementation of com.spotify.heroic.grammar.QueryParser, which is used to parse the Heroic DSL.

On the other hand, InfluxDB provides the following key features:

  • Time-Centric Functions
  • Scalable Metrics
  • Events

Heroic and InfluxDB are both open source tools. InfluxDB with 16.7K GitHub stars and 2.38K forks on GitHub appears to be more popular than Heroic with 710 GitHub stars and 89 GitHub forks.

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Advice on InfluxDB, Heroic

Anonymous
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
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
pionell

Sep 16, 2020

Needs adviceonMariaDBMariaDB

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
InfluxDB
Heroic
Heroic

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.

Heroic is Spotify's in-house time series database. It was built to address the challenges Spotify was facing with near real-time data collection and presentation at scale.

Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer
heroic-core contains the com.spotify.heroic.HeroicCore class which is the central building block for setting up a Heroic instance.; heroic-elasticsearch-utils is a collection of utilities for interacting with Elasticsearch. This is separate since we have more than one backend that needs to talk with elasticsearch.; heroic-parser provides an Antlr4 implementation of com.spotify.heroic.grammar.QueryParser, which is used to parse the Heroic DSL.; heroic-shell contains com.spotify.heroic.HeroicShell, a shell capable of either running a standalone, or connecting to an existing Heroic instance for administration.
Statistics
GitHub Stars
-
GitHub Stars
846
GitHub Forks
-
GitHub Forks
106
Stacks
1.0K
Stacks
5
Followers
1.2K
Followers
25
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, Heroic?

MongoDB

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

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

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

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

SQLite

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

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

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

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

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

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.

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