Time Series Database

TIME SERIES DATA IS EVERYWHERE

ENABLING ORGANIZATIONS TO MAKE BETTER DECISIONS

‘Time Series’ is not new. It has long been at the heart of commerce – most notably in the form of Financial market price ticks, but it is now equally widespread across industry and has evolved from minutes and seconds – to nano and milliseconds.

The connected world expands exponentially every year. Over the last ten years, we have experienced growth in the volume and velocity of data from ever-expanding cloud infrastructure, the emergence of 5G, and the rapid adoption of AI and machine learning across market trading platforms, smart meters, machine tools, and a myriad of IoT applications.

Fortunately, the constant stream of human and machine-generated data can now be captured and analyzed faster than ever before.

Businesses need to understand how to efficiently store and query the data and evaluate what platforms and analytic tools can help deliver the best-informed insights. More importantly, there’s an opportunity to use time-series data to make better-informed decisions and drive real business benefits.

WHAT IS A TIME SERIES DATABASE?

POWERFULLY MANAGE BIG DATA FOR TIMELY INSIGHTS 

Time series databases are specifically designed to capture and handle time-stamped data.

They can deliver significant improvements in storage space and performance over general-purpose databases and have the following key features:

• Optimized for time-based storage and retrieval.
• Every entry has a time stamp.
• Data gets appended rather than changed in situ.
• Different data sets can be associated by ‘time.’

Why does time series database matter? 

Time Series databases support improved, and faster decision-making based on what is occurring now, what happened in the past, and what is predicted to occur in the future.

A time series database can help:

• Automate applications and systems
• Deliver real-time and predictive analytics
• Provide operational intelligence across processes

Many businesses look at their big data applications purely through an “architecture” lens and miss the vital point that the unifying factor across all data is its dependency on time. For big data applications, the ability to capture and factor in “time” is the key to unlocking value.

Data exists and changes – in real-time, earlier today or further in the past. Time series databases are highly performant, scalable, and usable ways to handle exploding data sizes. They offer specialized features not supported in standard SQL and no-SQL languages and can enable your team to capture and perform the analysis required to support ML and AI models.

Time series datasets, databases and analytics can deliver a meaningful snapshot of your business – from any specific point in time.

Each piece of data exists and changes in real-time, earlier today or further in the past. However, unless they are all linked together in a way that firms can analyze, there is no way of providing a meaningful overview of the business at any specific point in time.

Some firms have struggled to introduce this due to the limitations of their technology. Some architectures don’t allow for time-based analysis and struggle with recording and querying it in a highly efficient way.  It’s a common issue resulting from opting for a seemingly safe technology choice.  It’s also one of the reasons why over the past 24 months that time-series databases (TSDBs) have emerged from software developer usage patterns as one of the fastest-growing categories of databases.

TREND OF THE LAST 12 MONTHS

WHY SHOULD I USE THE KDB+ TIME SERIES DATABASE?

KDB+ IS A TIME SERIES DATABASE OPTIMIZED FOR BIG DATA ANALYTICS

Kdb+, which underpins all KX solutions, is the world’s fastest and most efficient time series database and analytics engine, designed from the outset for high-performance, high-volume data processing and analysis. The columnar design of kdb+ and use of the same in-memory architecture for both real-time and historical data means it offers greater speed and efficiency than typical relational databases – read about our latest STAC-M3 Financial Services Benchmarking here. And its native support for time-series operations vastly improves both the speed and performance of queries, aggregation, and analysis of structured data.

Kdb+ is also different from other popular databases because it:

• can correlate streaming data with historical datasets to deliver contextual insights – in real-time.
• has a built-in array language, q, allowing it to operate directly on the data in the database, removing the need to export data to other applications for analysis.
• supports both time series and relational datasets, enabling joins and analysis across time series, referential, and meta data.
• fully uses the intrinsic power of modern multi-core hardware architectures and supports many interfaces with a simple API for easy connectivity to external graphical, reporting, and legacy systems.

For applications and critical decisions that require continuous and contextual intelligence, kdb+ accelerates your speed to business value. To experience the kdb+ difference, watch the demo, try the 12-month free kdb+ Personal Edition, or speak with our sales colleagues today.

High-Frequency Data Benchmarks for kdb+

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