InfluxDB vs MonetDB

Overview

InfluxDB

Stacks1.0K

Followers1.2K

Votes175

MonetDB

Stacks13

Followers35

Votes2

InfluxDB vs MonetDB: What are the differences?

Introduction: InfluxDB and MonetDB are both popular database management systems used for different purposes. Understanding the key differences between these two systems is crucial for selecting the best option for specific use cases.

1. Data Model: InfluxDB is a time-series database designed for storing and querying time-stamped data, making it ideal for IoT, monitoring, and analytics applications. On the other hand, MonetDB is a relational column-store database that excels in handling complex analytical queries on large datasets with multiple tables and relationships.

2. Query Language: InfluxDB uses InfluxQL, a SQL-like query language specialized for time-series data manipulation, while MonetDB supports standard SQL queries with additional advanced features like columnar storage optimization and vectorized query processing.

3. Performance: InfluxDB is optimized for high-throughput write and read operations on time-series data, providing excellent performance for real-time monitoring and data analysis. MonetDB, on the other hand, offers high performance for complex analytical queries involving joins, aggregations, and subqueries across large relational datasets.

4. Scalability and Horizontal Partitioning: InfluxDB provides built-in support for horizontal data partitioning and clustering to scale out across multiple nodes and handle growing volumes of time-series data efficiently. MonetDB also supports scalability through horizontal partitioning but focuses more on optimizing query performance through columnar storage and indexing strategies.

5. Use Cases: InfluxDB is commonly used in applications that require real-time data processing, event monitoring, IoT sensor data storage, and DevOps analytics. MonetDB is preferred for data warehousing, business intelligence, ad-hoc query analysis, scientific research, and other analytical workloads that involve complex queries on massive datasets.

6. Ecosystem and Integrations: InfluxDB has a rich ecosystem with support for various integrations, including Grafana, Telegraf, and Kapacitor, making it a popular choice for building monitoring and visualization solutions. MonetDB also offers integrations with tools like R, Python, and Tableau for advanced analytics and reporting capabilities.

In Summary, understanding the key differences between InfluxDB and MonetDB is essential for selecting the right database management system based on the specific requirements of time-series data processing or complex analytical queries.

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Advice on InfluxDB, MonetDB

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	MonetDB
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.	MonetDB innovates at all layers of a DBMS, e.g. a storage model based on vertical fragmentation, a modern CPU-tuned query execution architecture, automatic and self-tuning indexes, run-time query optimization, and a modular software architecture.
Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer	-
Statistics
Stacks 1.0K	Stacks 13
Followers 1.2K	Followers 35
Votes 175	Votes 2
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 HA or Clustering is only in paid version 1 Proprietary query language	Pros 2 High Performance

What are some alternatives to InfluxDB, MonetDB?

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.

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InfluxDB vs MonetDB: What are the differences?

InfluxDB vs MonetDB

Overview