Amazon Timestream for LiveAnalytics vs Kdb
A detailed comparison
Compare Amazon Timestream for LiveAnalytics and Kdb for time series and OLAP workloads
Learn About Time Series DatabasesChoosing the right database is a critical choice when building any software application. All databases have different strengths and weaknesses when it comes to performance, so deciding which database has the most benefits and the most minor downsides for your specific use case and data model is an important decision. Below you will find an overview of the key concepts, architecture, features, use cases, and pricing models of Amazon Timestream for LiveAnalytics and Kdb so you can quickly see how they compare against each other.
The primary purpose of this article is to compare how Amazon Timestream for LiveAnalytics and Kdb perform for workloads involving time series data, not for all possible use cases. Time series data typically presents a unique challenge in terms of database performance. This is due to the high volume of data being written and the query patterns to access that data. This article doesn’t intend to make the case for which database is better; it simply provides an overview of each database so you can make an informed decision.
Amazon Timestream for LiveAnalytics vs Kdb Breakdown
 |
 |
|
| Database Model | Time series database |
Time series and columnar database |
| Architecture | Timestream is a fully managed, serverless time series database service that is only available on AWS. |
Kdb can be deployed on-premises, in the cloud, or as a hybrid solution. |
| License | Closed source |
Closed source |
| Use Cases | Monitoring, observability, IoT, real-time analytics |
High-frequency trading, financial services, market data analysis, IoT, real-time analytics |
| Scalability | Serverless and automatically scalable, handling ingestion, storage, and query workload without manual intervention |
Highly scalable with multi-threading and multi-node support, suitable for large-scale data processing |
Looking for the most efficient way to get started?
Whether you are looking for cost savings, lower management overhead, or open source, InfluxDB can help.
Amazon Timestream for LiveAnalytics Overview
Amazon Timestream for LiveAnalytics is a fully managed, serverless time series database service developed by Amazon Web Services (AWS). Launched in 2020, Amazon Timestream for LiveAnalytics is designed specifically for handling time series data, making it an ideal choice for IoT, monitoring, and analytics applications that require high ingestion rates, efficient storage, and fast querying capabilities. As a part of the AWS ecosystem, Timestream seamlessly integrates with other AWS services, simplifying the process of building and deploying time series applications in the cloud.
Kdb Overview
kdb+ is a high-performance columnar, time series database developed by Kx Systems. Released in 2003, kdb+ is designed to efficiently manage large volumes of data, with a primary focus on financial data, such as stock market trades and quotes. It is built on the principles of the q programming language, which is a descendant of APL and K. The database is known for its speed, scalability, and ability to process both real-time and historical data.
Amazon Timestream for LiveAnalytics for Time Series Data
Amazon Timestream for LiveAnalytics is designed specifically for handling time series data, making it a suitable choice for a wide range of applications that require high ingestion rates, efficient storage, and fast querying capabilities. Its dual-tiered storage architecture, consisting of the Memory Store and Magnetic Store, allows Timestream to automatically manage data retention and optimize storage costs based on data age and access patterns. Additionally, Timestream supports SQL-like querying and integrates with popular analytics tools, making it easy for users to gain insights from their time series data.
Kdb for Time Series Data
kdb+ is designed to store time series data, making it a natural fit for applications that require high-speed querying and analysis of large volumes of data. Its columnar storage format allows for efficient compression and retrieval of time series data, while its q language provides a powerful and expressive means to manipulate and analyze the data. kdb+ is especially strong for financial data, though it can be used for other types of time series data as well.
Amazon Timestream for LiveAnalytics Key Concepts
- Memory Store: In Amazon Timestream for LiveAnalytics, the Memory Store is a component that stores recent, mutable time series data in memory for fast querying and analysis.
- Magnetic Store: The Magnetic Store in Amazon Timestream for LiveAnalytics is responsible for storing historical, immutable time series data on disk for cost-efficient, long-term storage.
- Time-to-Live (TTL): Amazon Timestream for LiveAnalytics allows users to set a TTL on their time series data, which determines how long data is retained in the Memory Store before being moved to the Magnetic Store or deleted.
Kdb Key Concepts
- q language: A high-level, domain-specific programming language used for querying and manipulating data in kdb+. It combines SQL-like syntax with a functional programming style.
- Columnar storage: kdb+ stores data in columns, rather than rows, which allows for faster querying and analysis of time series data.
- Tables: kdb+ stores data in tables, which are similar to relational tables, but with a focus on columnar storage and time series data.
- Splayed tables: A table storage format where each column is stored in a separate file, further enhancing query performance.
Amazon Timestream for LiveAnalytics Architecture
Amazon Timestream for LiveAnalytics is built on a serverless, distributed architecture that supports SQL-like querying capabilities. Its data model is specifically tailored for time series data, using time-stamped records and a flexible schema that can accommodate varying data granularities and dimensions. The core components of Timestream’s architecture include the Memory Store and the Magnetic Store, which together manage data retention, storage, and querying. The Memory Store is optimized for fast querying of recent data, while the Magnetic Store provides cost-efficient, long-term storage for historical data.
Kdb Architecture
kdb+ is a columnar, time series database that employs a custom data model tailored for efficient storage and querying of time series data. It does not use traditional SQL, but instead relies on the q language for querying and data manipulation. The architecture of kdb+ is designed for both in-memory and on-disk storage, with the ability to scale horizontally across multiple machines. The primary components of kdb+ are the database engine, the q language interpreter, and the built-in web server.
Free Time-Series Database Guide
Get a comprehensive review of alternatives and critical requirements for selecting yours.
Amazon Timestream for LiveAnalytics Features
Serverless architecture
Amazon Timestream for LiveAnalytics serverless architecture eliminates the need for users to manage or provision infrastructure, making it easy to scale and reducing operational overhead.
Dual-tiered storage
Timestream’s dual-tiered storage architecture, consisting of the Memory Store and Magnetic Store, automatically manages data retention and optimizes storage costs based on data age and access patterns.
SQL-like querying
Amazon Timestream for LiveAnalytics supports SQL-like querying and integrates with popular analytics tools, making it easy for users to gain insights from their time series data.
Kdb Features
High performance
kdb+ is known for its speed and performance, with its columnar storage format and q language allowing for rapid querying and analysis of time series data.
Scalability
kdb+ is designed to scale horizontally, making it suitable for handling large volumes of data across multiple machines.
q language
The q language is a powerful, expressive, and high-level language used for querying and manipulating data in kdb+. It combines SQL-like syntax with a functional programming style.
Amazon Timestream for LiveAnalytics Use Cases
IoT device monitoring
Amazon Timestream for LiveAnalytic’s support for high ingestion rates and efficient storage makes it an ideal choice for monitoring and analyzing data from IoT devices, such as sensors and smart appliances.
Application performance monitoring
Timestream’s fast querying capabilities and ability to handle large volumes of time series data make it suitable for application performance monitoring, allowing users to track and analyze key performance indicators in real-time and identify bottlenecks or issues.
Infrastructure monitoring
Amazon Timestream for LiveAnalytics can be used to monitor and analyze infrastructure metrics, such as CPU utilization, memory usage, and network traffic, enabling organizations to optimize resource utilization, identify potential issues, and maintain a high level of performance for their critical systems.
Kdb Use Cases
Financial data analysis
kdb+ is widely used in the financial industry for the storage and analysis of stock market trades, quotes, and other time series financial data.
High-frequency trading
kdb+ is a popular choice for high-frequency trading applications due to its high performance and ability to handle large volumes of real-time data.
IoT and sensor data
kdb+ can be used to store and analyze large volumes of time series data generated by IoT devices and sensors, though its primary focus remains on financial data.
Amazon Timestream for LiveAnalytics Pricing Model
Amazon Timestream for LiveAnalyticsv offers a pay-as-you-go pricing model based on data ingestion, storage, and query execution. Ingestion costs are determined by the volume of data ingested into Timestream, while storage costs are based on the amount of data stored in the Memory Store and Magnetic Store. Query execution costs are calculated based on the amount of data scanned and processed during query execution. Timestream also offers a free tier for users to explore the service and build proof-of-concept applications without incurring costs.
Kdb Pricing Model
kdb+ is a commercial product, with pricing depending on the deployment model and the number of cores or servers used. Kx Systems offers a free 32-bit version of kdb+ for non-commercial use, with limitations on the amount of memory that can be used. For commercial deployments and full-featured versions, users must contact Kx Systems for pricing details.
Get started with InfluxDB for free
InfluxDB Cloud is the fastest way to start storing and analyzing your time series data.
