OLAP

Teradata

Teradata is a massively parallel processing (MPP) relational database platform designed for large-scale enterprise data warehousing and analytics, originally s…

Vertica

Vertica is a columnar, massively parallel processing (MPP) analytics database designed for high-performance querying over very large datasets, originally creat…

Greenplum

Greenplum is an open-source massively parallel processing (MPP) data warehouse database built on top of PostgreSQL, designed for large-scale analytics and busi…

SAP HANA

SAP HANA is an in-memory, column-oriented relational database platform developed by SAP that combines transactional and analytical processing to power SAP's en…

Apache Pinot

Apache Pinot is an open-source, real-time distributed OLAP datastore built to answer analytical queries with very low latency over continuously streaming and b…

Materialize

Materialize is a streaming database that lets users write standard SQL, including joins and aggregations, against continuously changing data and get incrementa…

Firebolt

Firebolt is a cloud data warehouse built for high-performance, low-latency SQL analytics, designed to serve sub-second queries for analytics applications and d…

Databend

Databend is an open-source, cloud-native data warehouse written in Rust, designed to provide elastic, low-cost analytical SQL processing directly on data store…

OLTP

OLTP (Online Transaction Processing) refers to database systems and workloads optimized for large numbers of short, concurrent read/write transactions, such as…

OLAP

OLAP (Online Analytical Processing) refers to database systems and workloads optimized for complex, read-heavy analytical queries — aggregations, trends, and m…

Data Warehouse

A data warehouse is a centralized repository that stores structured, cleaned, and integrated data from multiple source systems, organized specifically to suppo…

Data Lakehouse

A data lakehouse is a data architecture that combines the low-cost, flexible storage of a data lake with the transactional reliability, schema enforcement, and…

ETL

ETL (Extract, Transform, Load) is a data integration process that pulls data from source systems, transforms it into a clean, structured format outside the tar…

ELT

ELT (Extract, Load, Transform) is a data integration pattern that loads raw data into a destination system first and performs transformation afterward, using t…

Data Mart

A data mart is a focused, subject-oriented subset of a data warehouse, scoped to the needs of a single business function or department such as sales, finance,…

Star Schema

A star schema is a dimensional data modeling technique in which a central fact table, holding measurable business events, is directly connected to multiple den…

Columnar Database

A columnar database stores data by column rather than by row, allowing analytical queries that scan and aggregate a small number of columns across many rows to…

OLTP (Online Transaction Processing)

OLTP (Online Transaction Processing) refers to database systems and workloads optimized for fast, high-volume execution of short, discrete transactions — typic…

OLAP (Online Analytical Processing)

OLAP (Online Analytical Processing) refers to database systems and workloads optimized for complex analytical queries — aggregations, multidimensional analysis…

Slowly Changing Dimension

A Slowly Changing Dimension (SCD) is a data warehousing technique for tracking and managing changes to dimension table attributes over time — such as a custome…

Star Schema vs Snowflake Schema: What is the Difference?

A star schema keeps each dimension table fully denormalized in one flat table around a central fact table, while a snowflake schema further normalizes those di…

What Are Fact and Dimension Tables in a Data Warehouse?

A fact table stores the measurable, numeric events of a business process — like sales amount or quantity sold — along with foreign keys to related dimensions,…

OLAP vs OLTP: What is the Difference?

OLTP (Online Transaction Processing) is optimized for many short, concurrent read/write transactions on individual rows, while OLAP (Online Analytical Processi…

Columnar Storage vs Row Storage: What is the Difference?

Row storage writes all columns of a single record contiguously on disk, making it fast to read or write an entire row at once, while columnar storage groups ea…

What is a Bitmap Index and When Should You Use One?

A bitmap index stores one bit array per distinct column value, where each bit position corresponds to a row and is set to 1 if that row holds that value, letti…

How to Design a Real-Time Analytics Dashboard?

A real-time analytics dashboard is designed around a streaming ingestion pipeline that continuously aggregates raw events into pre-computed rollups at multiple…

Columnar vs Row Storage: Which Should You Choose?

Row storage keeps all fields of one record physically together on disk, making it fast to read or write a whole record at once, while columnar storage groups t…