February 2022 Summaries

Praveen Viswanath, Enterprise Architect for Alpha Ori Technologies, discussed their experience using DataStax Astra DB in transforming marine logistics with big data in real-time. The company chose open-source Apache Cassandra® to build its SMARTship software, which collects and transmits over 5,000 data points every 30 seconds from various systems on a vessel. As the company grew, they turned to Astra DB for its fully managed, serverless database solution built on Cassandra, reducing operational overhead. This enabled real-time data streaming, fuel savings through route recommendations, and remote troubleshooting capabilities.

Sam Ramji and Barr Moses discuss the lack of an equivalent to DevOps for data engineers on the Open Source Data podcast. Moses, co-founder of data observability platform Monte Carlo, aims to provide data teams with the same insights as software engineers have had for years. She highlights the value of open source communities in addressing challenges like data trust, discoverability, and ownership. The concept of data observability is built on five pillars: freshness, distribution, schema, relationships, and lineage. Monte Carlo's platform helps data teams ensure their data is reliable and complete, enabling them to work as efficiently as software development teams running DevOps. Moses emphasizes the importance of customer-led growth in product development and shares her experience co-founding Monte Carlo with Lior Gavish. She encourages new graduates to find a strong fit between their passions and problem-solving abilities, emphasizing that life is too short for anything else.

Many organizations struggle to fully leverage their data, which remains an underutilized asset despite being a primary end goal of enterprise digitization and transformation. Companies have made progress in opening up data silos and automating processes with data, but significant gaps remain between potential value and actual achievement. The reasons for this include the creation of new data silos through platforms and tools, proliferation of IT systems, and difficulty accessing data rapidly enough to support digital business processes. To compete today, it's not enough to capture and store data; organizations must tap into real-time data streams directly as they move. Businesses that can use real-time data will offer compelling digital experiences and better automate operational decisions. Technology leaders should adopt new real-time data architectures in the cloud to break assets out of silos, create open and shared operational capabilities, and unlock their full potential.

Many IT organizations are adopting fully managed Database-as-a-Service (DBaaS) like Astra DB to reduce operational overhead and scale applications in the public cloud. This move brings agility to IT teams, enabling faster delivery of new innovations as a value add to customers. Companies can enjoy significant TCO savings by paying only for what they consume with serverless Astra DB, eliminating operational costs and burning down existing public cloud commits. DataStax CQL Proxy is an open-source tool that simplifies connecting applications to Astra DB without changing drivers or versions of Java. It works as a data proxy that handles the cloud network connection for Cassandra apps to Astra DB, auto-discovering and configuring communication with Astra DB. This separation of concerns between network management and query management makes it easier for companies to adopt fully managed Astra DB serverless on public clouds with minimal effort.

In this podcast episode, Sam Ramji and Jesse Anderson discuss the importance of having a data team in an organization to help drive business decisions with data-driven insights. They explore the problems that data teams encounter, such as accessing data and overcoming barriers posed by technology and cost. The conversation highlights the need for effective team structures within data teams, which should ideally consist of three different teams: data science, data engineering, and operations. Each team has a distinct responsibility to help get value from data. Anderson emphasizes that building a unified data team with clear roles and responsibilities is crucial for an organization's success in leveraging big data insights.

The DataStax Astra DB Data Loader simplifies the process of migrating historical data from Amazon DynamoDB to Astra DB. With a few clicks, users can load their data without downloading or setting up any additional software. This serverless loader is especially beneficial for write-intensive use cases like logging, time-series, IoT sensor applications, and web apps. Astra DB offers a consumption-based cost model with autoscaling capabilities, making it more cost-effective to operate in new geographic regions. Developers can connect their applications using familiar APIs or traditional binary language drivers. The platform supports various cloud environments, including AWS, Azure, Google Cloud, Kubernetes, and self-managed clouds. Astra DB offers a free trial with up to 80GB storage and 20 million read/write operations per month.

DataStax has announced a 50% reduction in the list price of write requests on Astra DB, effective February 1st. This move aims to improve cost performance value for write-intensive workloads compared to other DBaaS solutions in the market. Astra DB is a zero-ops managed service that combines the strengths of Apache Cassandra® with cloud offerings. Its serverless architecture ensures elasticity and cost efficiency, while its pricing model offers transparency and predictability. The new pricing will be automatically reflected for existing users from February 1st onwards, and new users can register for a free account to receive $300 worth of free usage every year.