How to load data from Tempo to Redis

Learn how to use Airbyte to synchronize your Tempo data into Redis within minutes.

Try Airbyte Cloud

Get a demo

Building your pipeline or Using Airbyte

Airbyte is the only open solution empowering data teams to meet all their growing custom business demands in the new AI era.

Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
Laborious and expensive
Brittle and inflexible

Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:

Reliable and accurate
Extensible and scalable for all your needs
Deployed and governed your way

All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Tempo connector in Airbyte

Connect to Tempo or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Redis for your extracted Tempo data

Select Redis where you want to import data from your Tempo source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Tempo to Redis in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Try Airbyte Cloud

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Old Automated Content

TL;DR

set up Tempo as a source connector (using Auth, or usually an API key)
set up Redis as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Tempo

Tempo is a global software-as-a-service company (SaaS) focused on providing companies with productivity and time management tools to drive more efficient and successful business. Products include resource planning, budget management, and world-class time tracking solutions for Jira (Tempo has claimed ownership to the #1 Jira time tracking app since 2010). Tempo drives business success by providing software that affords insights into teams’ productivity capabilities.

What is Redis

Redis is an open-source, in-memory data structure store that can be used as a database, cache, and message broker. It supports a wide range of data structures such as strings, hashes, lists, sets, and sorted sets. Redis is known for its high performance, scalability, and flexibility. It can handle millions of requests per second and can be used in a variety of applications such as real-time analytics, messaging, and session management. Redis also provides advanced features such as pub/sub messaging, Lua scripting, and transactions. It is widely used by companies such as Twitter, GitHub, and StackOverflow.

Integrate Tempo with Redis in minutes

Try for free now

Prerequisites

A Tempo account to transfer your customer data automatically from.
A Redis account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Tempo and Redis, for seamless data migration.

When using Airbyte to move data from Tempo to Redis, it extracts data from Tempo using the source connector, converts it into a format Redis can ingest using the provided schema, and then loads it into Redis via the destination connector. This allows businesses to leverage their Tempo data for advanced analytics and insights within Redis, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Tempo as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.

2. Click on the "Add Source" button in the top right corner of the screen.

3. In the search bar, type "Tempo" and select the Tempo source connector from the list of available connectors.

4. Enter a name for the connector and click on the "Next" button.

5. Enter your Tempo API credentials, including the API key and the base URL for your Tempo instance.

6. Test the connection to ensure that the credentials are correct and the connection is successful.

7. Select the data you want to replicate from Tempo, including the projects, tasks, and time entries.

8. Choose the replication frequency and the destination where you want to store the replicated data.

9. Click on the "Create Source" button to save the connector and start the replication process.

10. Monitor the replication process and troubleshoot any errors that may occur using the Airbyte platform's built-in tools and resources.

Step 2: Set up Redis as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the Redis destination connector and click on it.
4. You will be prompted to enter your Redis connection details, including the host, port, password, and database number.
5. Once you have entered your connection details, click on the "Test" button to ensure that your connection is working properly.
6. If the test is successful, click on the "Save" button to save your Redis destination connector settings.
7. You can now use the Redis destination connector to send data from Airbyte to your Redis database.
8. To set up a data integration pipeline, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector settings and configure your data integration pipeline.
10. Once your pipeline is set up, you can run it to start sending data from your source to your Redis database using the Redis destination connector.

Step 3: Set up a connection to sync your Tempo data to Redis

Once you've successfully connected Tempo as a data source and Redis as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Tempo from the dropdown list of your configured sources.
Select your destination: Choose Redis from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Tempo objects you want to import data from towards Redis. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Tempo to Redis according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Redis data warehouse is always up-to-date with your Tempo data.

Use Cases to transfer your Tempo data to Redis

Integrating data from Tempo to Redis provides several benefits. Here are a few use cases:

Advanced Analytics: Redis’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Tempo data, extracting insights that wouldn't be possible within Tempo alone.
Data Consolidation: If you're using multiple other sources along with Tempo, syncing to Redis allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Tempo has limits on historical data. Syncing data to Redis allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Redis provides robust data security features. Syncing Tempo data to Redis ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Redis can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Tempo data.
Data Science and Machine Learning: By having Tempo data in Redis, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Tempo provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Redis, providing more advanced business intelligence options. If you have a Tempo table that needs to be converted to a Redis table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Tempo account as an Airbyte data source connector.
Configure Redis as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Tempo to Redis after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

Easily address your data movement needs with Airbyte Cloud

Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team.

Get started with Airbyte for free

Talk to a data infrastructure expert

Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure.

Talk to sales

Improve your data infrastructure knowledge

Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.

Subscribe to newsletter

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that supports both incremental and full refreshes, for databases of any size.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Jean-Mathieu Saponaro

Data & Analytics Senior Eng Manager

"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"

Learn more

Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more

Alexis Weill

Data Lead

“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria. The value of being able to scale and execute at a high level by maximizing resources is immense”

Learn more

How to Sync Tempo to Redis Manually

Step 1:

Step 2:

Step 3:

Step 4:

Step 5:

Step 6:

Step 7:

Step 8:

FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Tempo?

What data can you extract from Tempo?

Tempo's API provides access to a wide range of data related to time tracking, resource management, and project management. The following are the categories of data that can be accessed through Tempo's API:

1. Time tracking data: This includes data related to time entries, such as start and end times, duration, and comments.

2. Resource management data: This includes data related to resources, such as employee information, team information, and workload.

3. Project management data: This includes data related to projects, such as project information, project status, and project timelines.

4. Billing and invoicing data: This includes data related to billing and invoicing, such as billing rates, invoices, and payment information.

5. Reporting data: This includes data related to reporting, such as timesheet reports, project reports, and resource reports.

6. Custom fields data: This includes data related to custom fields, such as custom fields for time entries, resources, and projects.

Overall, Tempo's API provides a comprehensive set of data that can be used to manage time, resources, and projects more effectively.

How do I transfer data from Tempo?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up Tempo to Redis as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Tempo to Redis and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Back to all tutorials

Databases

Finance & Ops Analytics

How to load data from Tempo to Redis

Learn how to use Airbyte to synchronize your Tempo data into Redis within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Tempo and Redis

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Tempo as a source connector (using Auth, or usually an API key)
set up Redis as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Tempo