Hevo Data is a no-code, bi-directional data pipeline platform specially built for modern ETL, ELT, and Reverse ETL Needs. It helps data teams streamline and automate org-wide data flows that result in a saving of ~10 hours of engineering time/week and 10x faster reporting, analytics, and decision making.
The platform supports 100+ ready-to-use integrations across Databases, SaaS Applications, Cloud Storage, SDKs, and Streaming Services. Over 500 data-driven companies spread across 35+ countries trust Hevo for their data integration needs.
Try Hevo today and get your fully managed data pipelines up and running in just a few minutes.
Hevo Data is recommended for businesses of all sizes that are seeking an easy-to-use platform for automating their data integration processes. It is particularly beneficial for teams that may not have extensive technical expertise but still need to manage complex data environments effectively. Companies looking for a scalable solution to handle real-time data streaming and transformation will also find Hevo Data beneficial.
Based on our record, Apache Spark should be more popular than Hevo Data. It has been mentiond 70 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Some popular tools for data extraction are Airbyte, Fivetran, Hevo Data, and many more. - Source: dev.to / 6 months ago
In a previous article, we used open-source Airbyte to create an ELT pipeline between SingleStoreDB and Apache Pulsar. We have also seen in another article several methods to ingest MongoDB JSON data into SingleStoreDB. In this article, we’ll evaluate a commercial ELT tool called Hevo Data to create a pipeline between MongoDB Atlas and SingleStoreDB Cloud. Switching to SingleStoreDB has many benefits, as described... - Source: dev.to / over 2 years ago
One of my customers just purchased Precisely to extract from their iSeries machines into Snowflake. Hevo can also do it. Source: over 2 years ago
I've been looking at Hevo data as well, and they certainly make the setup/maintenance a lot easier, but they have a latency of 5-10 minutes. What's the minimum lowest latency that can be achieved with aws for syncing dynamodb to redshift? Source: almost 3 years ago
Don't decide on something without looking at Hevo - I've used this in two organisations now and can't speak more highly of it. Cheap, super simple to use, and super configurable if you want to get into the nitty gritty. Source: about 3 years ago
Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / about 2 months ago
Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / about 2 months ago
One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 3 months ago
[1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 3 months ago
If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 4 months ago
Fivetran - Fivetran offers companies a data connector for extracting data from many different cloud and database sources.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Stitch - Consolidate your customer and product data in minutes
Hadoop - Open-source software for reliable, scalable, distributed computing
Improvado.io - Improvado is an ETL platform that extracts data from 300+ pre-built connectors, transforms it, and seamlessly loads the results to wherever you need them. No more Tedious Manual Work, Errors or Discrepancies. Contact us for a demo.
Apache Storm - Apache Storm is a free and open source distributed realtime computation system.