![]() ![]() ![]() So people will migrate their data out of those data warehouse technologies into ClickHouse for aggregations and reporting. But the use cases that we're seeing now, we are seeing companies that will migrate from traditional data warehouse technologies, other what many would consider legacy technologies like Teradata and other cloud-based technologies, like BigQuery and RedShift.Īnd then we see a lot of coexistence where there are very efficient data warehouse storage engines, but they perhaps don't offer the same responsiveness in terms of query execution. So I think there's some pattern recognition there we could consider. We still think, for example, that is a great job in terms of the separation of computing and storage and really making their cloud-based data warehouse service more like an API endpoint. ![]() It has a number of other useful extensions. Currently, our joint syntax now follows the SQL standard. In 2018, ClickHouse introduced batch updates and deletes in preparation for GDPR. And so that would now be a bit of a myth to claim that, and thus there's no finish line, obviously, when it comes to these specific feature sets. Since then, the team has made considerable strides in improving both of those baskets. I'll start by granting you that, yes, when ClickHouse was originally opened sourced in 2016, it indeed only had partial limited support for SQL joins and mutable data. ![]() Do you think that we should really think about ClickHouse doubling down - Warehouse solution to compete with other players in this space - or do you think that's limiting in how you describe the technology? To get the results set from a SQL query across a dataset as measured in petabytes, and to get that results in the same amount of time it takes for a webpage to load - let's say two hundred milliseconds - is really where people have found ClickHouse is unique in its architecture and performance. If you think of web and mobile analytics, BI, observability, and IOT, where the data set is massive, to begin with, but continues to grow over time and all of that data, the historical data and the latest data that's streaming in, needs to be queried and analyzed simultaneously. This can be a challenge in practice for large-scale use cases. And I think the primary two benefits that we were hearing from the community are largely around speed, performance, and then storage efficiency for real-time queries across a number of attributes in high volume workloads. Learn how to integrate Metabase data with the rest of your marketing data using Improvado.Well, let me start by saying it's essentially a database technology. Create the visual reports you need and squeeze the most out of your data. Integration with dozens of other SQL databases.Įnhance your data manipulation abilities with Metabase by pairing it with Improvado.Set individualized permissions for each user in the database.Utilize custom filters to easily sort through your database.Integrate with other database software,including Microsoft SQL Server and Amazon Redshift.Schedule individualized questions and goals for your projects.Build unique dashboards for each of your datasets.Consolidate all your data into one convenient database.Dedicated Customer Success Manager included.Extract data via API, FTP, S3, CSV Uploads, Google Spreadsheets or email.Sync hard-to-extract data sources, like Snapchat, LinkedIn, and Sizmek and so on.Automatically update Metabase dashboards.Regularly scheduled reports (pulses) will keep everyone up to date. The possibility of easily sharing dashboards through multiple means will help to implement the analytics results quickly. Metabase can optimize the performance of a team working together, as anyone, regardless of technical background, can ask questions and get simple, understandable results.It's possible to save the X-rays you find helpful or disable them altogether. The X-ray function will make automatic data explorations and comparisons. It's also possible to organize dashboards in collections, use them with widgets to filter data in different questions, and set customized destinations after a click. After some time, Metabase will also provide customized questions for you. The Notebook editor will help you to create detailed questions. After asking questions about the data, you can group the received results (charts) into an unlimited number of dashboards. Metabase demonstrates to you a list of connected databases and offers automatic explorations of data.You can simply ask questions, which, later on, will be possible to save or share with colleagues. For doing that, you won't even need to write an SQL query. Metabase is a business intelligence tool that will help you to browse your data, analyze it, and represent it in an easily comprehensible format. Exploring All Your Marketing Data in Metabase ![]()
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