Kdb+ vs QuestDB: Old Guard Meets New Challenger

Kdb+ was designed in the 1990s primarily for financial markets and is used heavily by investment banks and hedge funds for ultra-low latency time-series processing.

In this blog post, we’ll explore QuestDB (its installation process step by step and some sample data queries)—an open-source time-series database designed for real-time analytics. Known for its SQL compatibility, QuestDB is gaining popularity across various industries.

SQL compatibility makes QuestDB easier to learn and integrate into existing workflows, especially for teams without prior experience in specialized languages like q.

Installing Steps

• Open your Terminal in MacOS.

• Run the below install command:

  
  

brew install questdb

• After installation you can start QuestDB by typing

  
  

brew services start questdb

You will see the pop-up showing background items added and questdb now is running in the background.

Now open your browser and go to

http://localhost:9000

to access the QuestDB web console.

You should now have access to QuestDB interface.

Now, I will create a table and insert some data.

In order to create a table I will use the below SQL.

When I hit 'run query' I see my table 'trades' is created succesfully.

Now I will enter some data into 'trades'.

I will query the timestamps of the trades I previosly entered.

I want to ingest additional data by uploading a .csv file.

(As a prerequisite, make sure QuestDB is running in the background—either via Homebrew or through a connected app.)

I’ll be using the trades table. Keep in mind that QuestDB will automatically create the table if it doesn't already exist.

I ran a basic sample query listing the bid price and timestamps when the reason equals 'Liquidity Event'.

QuestDB offers several options for connecting to different applications, importing your own data, and generating random data. So far, the installation process and data querying have been straightforward.

Conclusions

As mentioned at the beginning, QuestDB uses SQL, making it approachable for most developers familiar with relational databases. In contrast, kdb+ relies on its proprietary q language, which has a steeper learning curve.

Additionally, QuestDB is open source with no licensing barrier, allowing users to get started quickly without cost concerns. It supports modern deployment methods such as Docker, Kubernetes, and cloud platforms like AWS.

Overall, QuestDB offers a more accessible and flexible option for teams looking to work with time series data using familiar tools.