Best OLAP Databases for Astro

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The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

Apache Druid, an open-source distributed data store, is Apache Druid. Druid's core design blends ideas from data warehouses and timeseries databases to create a high-performance real-time analytics database that can be used for a wide range of purposes. Druid combines key characteristics from each of these systems into its ingestion, storage format, querying, and core architecture. Druid compresses and stores each column separately, so it only needs to read the ones that are needed for a specific query. This allows for fast scans, ranking, groupBys, and groupBys. Druid creates indexes that are inverted for string values to allow for fast search and filter. Connectors out-of-the box for Apache Kafka and HDFS, AWS S3, stream processors, and many more. Druid intelligently divides data based upon time. Time-based queries are much faster than traditional databases. Druid automatically balances servers as you add or remove servers. Fault-tolerant architecture allows for server failures to be avoided.

You can query billions upon billions of rows with an in-memory columnar database and MPP architecture. Queries are distributed across all cluster nodes, allowing for linear scaling and advanced analytics. The fastest database for data analytics is made up of MPP, columnar storage, and in-memory. You can analyze data anywhere it is stored, whether you are using SaaS, cloud, hybrid, or on-premises deployments. Automatic query tuning reduces overhead and maintenance. You get more power for a fraction of the normal infrastructure costs with seamless integrations and performance efficiency. This social networking company was able to increase its performance by using smart, in-memory query processing. They processed 10B data sets per year. A single data repository and speed-engine to accelerate critical analytics, improving patient outcomes and the bottom line.

Presto is an open-source distributed SQL query engine that allows interactive analytic queries against any data source, from gigabytes up to petabytes.

Apache Kylin™, an open-source distributed Analytical Data Warehouse (Big Data), was created to provide OLAP (Online Analytical Processing), in this big data era. Kylin can query at near constant speed regardless of increasing data volumes by renovating the multi-dimensional cube, precalculation technology on Hadoop or Spark, and thereby achieving almost constant query speed. Kylin reduces query latency from minutes down to a fraction of a second, bringing online analytics back into big data. Kylin can analyze more than 10+ billion rows in less time than a second. No more waiting for reports to make critical decisions. Kylin connects Hadoop data to BI tools such as Tableau, PowerBI/Excel and MSTR. This makes Hadoop BI faster than ever. Kylin is an Analytical Data Warehouse and offers ANSI SQL on Hadoop/Spark. It also supports most ANSI SQL queries functions. Because of the low resource consumption for each query, Kylin can support thousands upon thousands of interactive queries simultaneously.

Pinot is designed to answer OLAP questions with low latency and immutable data. Pluggable indexing technologies: Sorted Index (Bitmap Index), Inverted Index. Trino and PrestoDB are both available for querying, but joins are not currently supported. SQL-like language that supports selection and aggregation, filtering as well as group by, order, and distinct queries on data. Both an offline and a real-time table are possible. Only use real-time table to cover segments where offline data is not yet available. Customize anomaly detection flow and notification flow to detect the right anomalies.