Login

Please login for an individual price calculation.

Forgot Password?

Always stay up to date

With our e-mailings you will receive regular information about products, events, services and Balluff.

REGISTER AS A COMPANY

We will check whether you already have a customer number with us in order to link your new online account with it.

Register
Products
Service & Support
Industries & Solutions
Company

Influx Database vs Structured Query Language Database

Which database to use for your application

Sam Thompson
10 2025 | 08:27 Clock

Reading Time: minutes

As we progress in the Industrial Internet of Things (IIOT), choosing the right database is an important part of managing applications. Two common options are Influx Database (InfluxDB), a time-series database, and Structured Query Language (SQL) database, often called Sequel. Both store and retrieve data, but they are designed with very different priorities in mind.

Main Differences

The most fundamental difference is in the data model. SQL databases use the relational model, where information is stored in tables with rows and columns. Relationships between tables ensure consistency and allow complex queries. This makes SQL databases well suited for structured business data such as orders and invoices.

Influx Database, on the other hand, is built specifically for time series data. Every entry is automatically timestamped and organized into measurements, tags, and fields. This design makes it efficient at handling values that change over time, such as sensor readings, logs, or condition monitoring metrics.

The query languages also differ. SQL databases use Structured Query Language, a long-established standard for joins, filtering, and aggregations. Influx Database introduced Influx Query Language (InfluxQL), which looks like SQL, and later developed Flux, a functional scripting language designed for time-based analysis such as moving averages.

SQL databases are optimized for transactional workloads where frequent updates, multi table relationships, and consistency are required. Influx Database is optimized for very high write throughput, potentially millions of new data points per second, while enabling fast queries across time intervals.

Data retention strategies also separate the two. SQL databases typically hold data indefinitely unless deleted or archived by the administrator. Influx Database includes built in retention policies that can automatically remove or compress older data, which is more relevant when monitoring machine health where recent data matters most.

Overlapping Features

Although different in design, Influx Database and SQL databases share important similarities. Both rely on structured queries to filter and analyze data. Both use indexing strategies to improve performance, with SQL focusing on keys and Influx Database indexing time and tags. Both can integrate with visualization platforms such as Grafana.

When to Use Each

Influx Database is the better choice when data is time stamped and arrives in large volumes. Examples include industrial equipment monitoring, application performance metrics, and event logging. In these cases, automatic retention makes storage efficient while still supporting real-time queries.

SQL databases remain the preferred option for relational and transactional needs. Business systems with customers, orders, and payments rely on the relational model to maintain integrity. Financial and accounting applications also depend on the strict consistency guarantees of SQL. When data must be stored long term and analyzed across many related tables, SQL databases are the better solution.

Conclusion

Influx Database and Structured Query Language databases are not direct replacements for each other but complementary tools. Influx Database excels at handling high volume time series data, while SQL databases are ideal for transactional applications. The best choice depends on the problem.  Use Influx Database for monitoring and metrics and use Structured Query Language databases for business operations and transactions. In many cases, organizations benefit by combining both, letting each database type serve its intended purpose.

Keywords

  • Industry 4.0
  • Internet of Things

Did you like this post?

3

Share this post

Author

Sam Thompson

Sam Thompson


7 Contributions

Comment

Discover related topics

More from the author

Energy consumption labeling
Energy consumption labeling

EPREL - European Product Database for Energy Labeling

Do you have any questions or suggestions? We are at your disposal.

For all questions concerning commercial topics such as quotations, orders, and delivery times, our inside sales department will be happy to support you: [email protected]

For Aftersales, Technical Support, Applications and
Product Inquiries we will be happy to support you: [email protected]

Feel free to contact us directly by telephone:

Inside Sales 859-727-2200 - press 1
Presales Tech Support 859-727-2200 - press 2
Aftersales Tech Support 859-727-2200 - press 3


Balluff Inc.

8125 Holton Dr.
Florence, KY 41042

Free sample product

In order to add a free sample product to the cart we will need to remove all the normal products from the cart. Are you sure you want to continue