article thumbnail

Comparing ClickHouse vs Rockset for Event and CDC Streams

Rockset

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. ClickHouse has several storage engines that can pre-aggregate data.

MySQL 52
article thumbnail

Case Study: Is Your NoSQL Data Hindering Real-Time Analytics? Savvy Solved It with Rockset.

Rockset

All interactions are streamed in the form of semi-structured events into Firebase’s NoSQL cloud database, where the data, which includes a large number of nested objects and arrays, is ingested. We ended up deploying a real-time analytics platform, Rockset , on top of MongoDB. It feels like magic!

NoSQL 52
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

A Quick Primer on Indexing in Rockset Rockset allows users to connect real-time data sources — data streams (Kafka, Kinesis), OLTP databases (DynamoDB, MongoDB, MySQL, PostgreSQL) and also data lakes (S3, GCS) — using built-in connectors. You can also optionally use WHERE clauses to filter out data.

SQL 52
article thumbnail

Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. Transmitting out-of-order data is not the issue.

article thumbnail

Python for Data Engineering

Ascend.io

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

article thumbnail

Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. In the event that they are not the same, what are the difference s? Gen 2 Azure Data Lake Storage . Data lakes can also be organized and queried using other technologies, such as .

article thumbnail

The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

This scenario involves three main characters — publishers, subscribers, and a message or event broker. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Kafka cluster and brokers.

Kafka 93