In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.
Zilliz Unveils Zilliz Cloud, the New Industry Standard for Vector Database as a Service
Zilliz, provider of the leading vector database built on Milvus for enterprise-ready AI, today announced that Zilliz Cloud is generally available and ready for enterprise production workloads with a 99.9 percent guaranteed uptime service level agreement (SLA). Featuring the Zilliz team’s expertise in running some of the largest-scale and most complicated vector similarity search in production, the fully-managed service makes it easy for companies to deploy and run their image retrieval, video analysis, recommendation engines, targeted ads, customized search, smart chatbots, fraud detection, network security, new drug discovery, and many other AI applications at scale.
“We started Zilliz with building an open-source solution Milvus to bring the capability of vector database to the masses. Now with Zilliz Cloud, we’re thrilled to offer the experience valued by our open-source users in an even more simplified manner with a fully-managed cloud service. It takes only a few clicks to start up your own instance on Zilliz Cloud, and less than a day to build a highly optimized vector similarity search service to extract valuable insights. We believe that the combination of extraordinary performance and peerless scalability delivers significant benefits to our customers,” says Charles Xie, founder and CEO of Zilliz.
Qlik Launches Qlik Cloud Data Integration to Enable a Real-Time Enterprise Data Fabric With Automated Data Movement and Advanced Transformations
Qlik® launched Qlik Cloud® Data Integration, its Enterprise Integration Platform as a Service (eiPaaS) offering to fuel enterprise data strategies through a real-time data integration fabric that connects all enterprise applications and data sources to the cloud.
“Improving the access, real-time movement and advanced transformation of data between sources and systems across the enterprise is crucial to organizations realizing the full power of their data,” said James Fisher, Chief Product Officer at Qlik. “Qlik Cloud Data Integration helps create that real-time fabric between any data source, target and destination, leveraging the power of the cloud to enable everyone in the enterprise to act with certainty through data.”
Smartling’s Translation Platform Enhanced with Expanded Neural Machine Translation Hub
Smartling, the enterprise translation solutions company, announced a major product expansion for its Neural Machine Translation (NMT) Hub, making it widely available for all Smartling customers. Smartling is uniquely positioned to deliver best-quality instant translations, using their platform data to power AI-driven decisions. This is possible using a combination of technologies such as Neural Machine translation, which is capable of providing translation quality comparable to that of human translation, their proprietary Machine Learning models and “human-in-the-loop” delivery platform. Together, Smartling is able to provide customers with industry leading
translation quality and speed that integrates the use of humans with AI to meet the challenges
and scale of any content translation request at a fraction of the cost.
“We’re very excited to finally share the NMT Hub with our wider customer base,” said Olga Beregovaya, VP of Machine Translation and AI at Smartling. “After testing successfully with a portion of our users, I’m confident they will be pleased with how easy content translation will be across the board. It’s integrated with leading machine translation engines and provides additional Natural Language Processing (NLP) functionality to further refine translation quality. We’ve managed to bring one of the most powerful cloud-based, flexible, all-in-one platforms to the market, while offering workflow, integration and file handling features.”
Snowplow launches Data Product Accelerators, Snowplow BDP Cloud and Enterprise updates
Snowplow, a leader in Data Creation and behavioral data, has announced the availability of the first of its Data Product Accelerators (DPAs)— recipes designed to help accelerate the journey from ideation to outcome when designing business-critical data products. The company has also announced preview availability of new offerings within its Behavioral Data Platform (BDP) portfolio.
Snowplow DPAs mark the next evolution of Data Creation, the category founded by Snowplow that involves the deliberate creation of data to power AI and advanced data applications. These DPAs lay the foundation for the fast creation of data apps, providing a step-by-step guide or referencing data architecture to effortlessly deliver high-impact use cases that solve specific business needs or problems.
“Across industries, organizations know they need to be doing more with data. They know that simply extracting data is not enough—they need to create data that’s meaningful to their unique situation. Yet, in an emerging field like this, we felt that we could do more to share best practices and get outcomes into the hands of Data teams and their organizations. These DPAs will help our customers to easily understand and experience the value of Snowplow, in a context that is highly meaningful to them,” said Snowplow President, Chief Product and Marketing Officer, Nick King.
mParticleannounces Warehouse Sync, the convenience of reverse-ETL with the power of a real-time CDP
mParticle, a customer data platform, announced that it is expanding its catalog of data sources to include direct ingestion from data warehouses beginning with Snowflake (NASD: SNOW) followed by support for Google BigQuery, Amazon RedShift, and Microsoft Azure. Warehouse Sync delivers cost and time-savings for data teams that want to maximize their existing data infrastructure and solve the complexities of utilizing customer data for personalization.
“The cloud data warehouse is an important source of rich customer data which teams need to incorporate into their data strategies,” said Michael Katz, CEO and co-founder of mParticle. “The customer data stack and the data engineering stack are beginning to converge, which we believe will unlock new opportunities for teams of all sizes, and we’re excited to expand our offering with this latest feature.”
ThoughtSpot for Sheets Launches to Bring Self-service Analytics to Spreadsheets
ThoughtSpot, the Modern Analytics Cloud company, announced the launch of ThoughtSpot for Sheets, an entirely new web plug-in that brings modern, true self-service analytics directly to data in Google Sheets. With ThoughtSpot for Sheets, users simply install a free plugin app for Google Sheets, and then can instantly begin analyzing all their data in these sheets through search. Built and run entirely in the browser, ThoughtSpot for Sheets requires no data modeling, technical skills, or existing architecture. Users simply install, connect, and start searching.
“ThoughtSpot is the platform for the masses, for everyday people to be able to ask questions of their cloud data and get reliable answers back instantly. But we know to truly advance our mission of building a more fact-driven world, we must go beyond the more robust, mature cloud data platforms, and be anywhere data lives. That includes spreadsheets,” said Sumeet Arora, Chief Development Officer, ThoughtSpot. “ThoughtSpot for Sheets makes it possible for any individual to experience the power of self-service analytics and get answers, exactly when and where they need them.”
Couchbase Introduces New Developer Experience for Capella, Empowering Users to More Easily Build Next Generation Applications
Couchbase, Inc. (NASDAQ: BASE), the cloud database platform company, announced new enhancements to its database-as-a-service (DBaaS) Couchbase Capella. The newly designed Capella user experience is inspired by popular technologies that millions of developers already use to build modern applications. Because of this sense of familiarity, the new Capella experience boosts productivity so developers can more easily build next-generation applications. And with Capella, organizations also benefit from best-in-class price performance.
“As customers continue to invest in digital transformation, developers who are building modern applications need technologies that make them more productive. To address this market need we have invested in removing friction for developers, enhancing their experience and enabling greater agility with this latest Capella release,” said Scott Anderson, senior vice president of product management at Couchbase. “We are seeing enthusiastic customer receptivity and growing momentum for Capella, and I’m proud of our investments in advancing its flexibility and ease-of-use. We are making Capella more accessible than ever before to developers and look forward to seeing what next-gen applications will be built upon our cloud database platform.”
Pinecone launches advanced hybrid search functionality
Pinecone Systems Inc., a machine learning (ML) search infrastructure company, announced the release of an innovative keyword-aware semantic search solution that enables the world’s most accessible and advanced combination of semantic and keyword search results. “Vector search” allows companies to provide relevant results based on semantic, or similar meanings, as opposed to simple keyword-based searches. At the same time, keywords still matter in searches involving uncommon words like names or industry-specific terms. With few exceptions, companies have to choose between semantic search and keyword search, or running both systems in parallel. Neither of these options is ideal. When companies choose one or the other, the results are not as complete as they could be, and when they run both systems in parallel and try to combine the results, cost and complexity goes up significantly.
“Our research shows that keyword-aware semantic search is superior to either semantic search or keyword search separately. This release finally allows businesses to provide their users with the most relevant possible results no matter how specific the query or how unique the topic,” said Edo Liberty, Founder and CEO of Pinecone.
Soda Cloud Self-Serve Launches to Unite Data Consumers and Data Producers with Data Quality Agreements
Soda, the provider of open-source data reliability tools and cloud data quality platform, has released a new set of self-serve features and capabilities for Soda Cloud that unites data consumers and data producers to ensure that the data being produced is both useful and trustworthy. Built to empower the data consumers who are creating new products using data, and the teams responsible for producing data, Self-Serve enables the consumers of data to collaborate with data producers and owners to create data quality agreements that define and align expectations for the use of high-quality, reliable data, and ensures that it is always fit-for-purpose.
“Data teams today are crying out for a simpler way to manage their organization’s data quality in order to create a better data culture and, ultimately, to improve business processes,” said Maarten Masschelein, CEO, Soda. “To this end, we are delighted to announce the general availability of Soda Cloud Self-Serve, another big step toward unifying data teams across the data product lifecycle and empowering them to confidently use and share data. Feedback from our preview earlier this year showed users were particularly excited to be able to use Soda Cloud Self-Serve to help democratize data quality checks and promote the concept of improved data quality right across the organization. I am pleased that the Soda Cloud Self Serve will both empower data engineers to improve the reliability of transactional automations with data, and improve wider data operations by simplifying the implementation of best-practice workflows to efficiently work with data as a team.”
AWS Announces Amazon Neptune Serverless
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced Amazon Neptune Serverless, a new serverless option for Amazon Neptune that automatically scales to support unpredictable and business-critical graph database workloads. Amazon Neptune is a fast, reliable, and fully managed service that makes it easy to build and run applications that need a graph database to efficiently store and query complex and highly connected datasets. Amazon Neptune Serverless includes Amazon Neptune’s advanced capabilities for high availability, performance, and resiliency. There are no upfront commitments or additional costs to use Amazon Neptune Serverless, and customers only pay for the database resources used. To get started with Amazon Neptune Serverless, visit aws.amazon.com/neptune/serverless.
“Customers tell us that they appreciate the ability to use Amazon Neptune to understand complex relationships among highly connected data points. They have also asked us to take care of the heavy lifting associated with managing capacity and optimizing for cost and performance,” said Swami Sivasubramanian, vice president of Databases, Analytics, and Machine Learning at AWS. “Now, with Amazon Neptune Serverless, customers have a graph database that automatically provisions and seamlessly scales clusters to provide just the right amount of capacity to meet demand, allowing them to build and run applications for even the most variable and unpredictable workloads without having to worry about provisioning capacity, scaling clusters, or incurring costs for unused resources.”
DataStax Delivers Stargate V2: Unlocking Apache Cassandra Data to Serve Billions of Devices in Real Time
DataStax, the real-time data company, announced the launch of Stargate v2, a new version of the award-winning open source data gateway that gives application developers the freedom to build real-time applications for Apache Cassandra using their API of choice. Stargate v2, which is available as open source software and part of the DataStax’s Astra DB database-as-a-service, now features a high-performance gRPC API that enables developers to easily scale Cassandra data to serve billions of global devices with speed, in real time.
“This year downloads of open source Stargate for Apache Cassandra 4.0 have increased 7x,” said Ed Anuff, CPO, DataStax. “Stargate is empowering developers to pick the data model that best suits their needs and evolve it dynamically, leveraging the power of Cassandra – the most scalable database in existence. With Stargate, developers no longer have to learn everything in order to do anything. They can focus on their particular areas of expertise and interest as they develop high-growth applications.”
Mezmo Unveils Observability Pipeline to Enhance the Value of Data
Mezmo, an observability data platform provider, unveiled its Observability Pipeline, which enables teams to control, enrich, and correlate machine data for actionable insights and faster decisions. The massive volume, variety, and difficult-to-consume nature of machine data generated in modern environments create immense challenges for DevOps, SRE, and security teams, who struggle to control escalating costs and use their data to drive any meaningful action. The inability to use this data to its fullest increases security risks, negatively impacts customer experience, and drains resources. Mezmo’s Observability Pipeline helps organizations better control their observability data and deliver increasing business value. It centralizes the flow of data from various sources, adds context to make data more valuable, and then routes it to destinations to drive actionability.
“Data provides a competitive advantage, but organizations struggle to extract real value. First-generation observability data pipelines focus primarily on data movement and control, reducing the amount of data collected, but fall short on delivering value. Preprocessing data is a great first step,” said Tucker Callaway, CEO, Mezmo. “We’ve built on that foundation and our success in making log data actionable to create a smart observability data pipeline that enriches and correlates high volumes of data in motion to provide additional context and drive action.”
InfluxData Deploys Next-Generation InfluxDB Time Series Engine with Unlimited Scale
InfluxData, creator of a leading time series platform InfluxDB, announced the deployment of its next-generation time series engine. The new engine reimagines InfluxDB as a columnar real-time data platform, delivering high-volume data ingestion with unbounded cardinality, optimized for the full range of time series data. InfluxData also adds SQL language support for queries, bringing the hugely popular data programming language to InfluxDB for the first time. With the introduction of SQL, InfluxDB now enables broad analytics use cases through business intelligence and machine learning tools.
“InfluxData’s new storage engine is a significant advancement in how our customers work with time series data, transforming InfluxDB into a real-time analytics platform,” said Paul Dix, Founder and CTO, InfluxData. “Limited scale is a thing of the past. Now developers can run unlimited time series workloads in InfluxDB and contextualize data by any dimension and without restrictions, improving performance for the largest applications in IoT, cloud observability, and other resource-intensive analytics applications.”
TruEra Launches First Automated Test Harness for ML Models with TruEra Diagnostics 2.0 Release
TruEra, which provides the suite of AI Quality management solutions for managing model performance, explainability, and societal impact, launched TruEra Diagnostics 2.0, a major update to its TruEra Diagnostics solution, incorporating the first-ever automated test harness for AI models that includes root cause analysis. The new systematic testing features in TruEra Diagnostics 2.0 help enterprises to get models into production faster by providing comprehensive model evaluation that promotes quality and transparency, accelerating model development and approval.
“We are seeing huge demand from enterprises for comprehensive AI Quality management solutions,” said Will Uppington, co-founder and CEO of TruEra. “AI development is where enterprise software was in the early days of its adoption, before automated testing was ubiquitous. We strongly believe that better testing and monitoring for AI models will increase their impact and accelerate their adoption, just as it sped the adoption of enterprise software years ago. There’s a clear need for better and more systematic AI model testing and debugging, and we’re proud to be first to market with these capabilities.”
Lightstep from ServiceNow Delivers Fully Observable Kubernetes Applications with New Unified Query Language
ServiceNow (NYSE: NOW), a leading digital workflow company making the world work better for everyone, announced the general availability of Lightstep UQL (Unified Query Language) which will help companies extend visibility across Kubernetes applications. Using shift‑left observability directly in code, DevOps teams help ensure Kubernetes applications are ‘born’ fully observable and proactively enforce consistency, maintainability, and reproducibility best practices – as opposed to having SREs build dashboards on the fly.
“Engineers today can leverage observability‑as‑code for more powerful and flexible insights into the health and performance of their cloud‑native applications,” said Ben Sigelman, general manager and co‑founder of Lightstep from ServiceNow. “This is especially important when thinking about modern architectures like Kubernetes, which are highly complex and dynamic. Lightstep UQL works to ensure that every Kubernetes application deployed is fully instrumented and observable by default.”
D2iQ Simplifies Artificial Intelligence and Machine Learning Operations with Industry-First Enhancements to Kaptain AI/ML Platform
“While more organizations are adopting Kubernetes to scale workloads in production environments, the growing complexities and lack of technical skills are holding back the full potential of AI/ML deployments,” said Deepak Goel, Chief Technology Officer at D2iQ.
Lytics Debuts Conductor to Empower Businesses to Unify and Activate Customer Data
Lytics, a next generation customer data platform (CDP), announced the launch of Conductor, the centerpiece of Lytics Composable CDP. Conductor is Lytics Customer Data Infrastructure (CDI) product that connects and unifies customer data, for better results across the marketing and data stack, to improve ROI and reduce costs.
“Every company has customer data that is underperforming and in today’s market they can’t afford to,” said Jascha Kaykas-Wolff, President, Lytics. “With the introduction of Conductor, Lytics makes it even easier to grab more data from any channel or touchpoint in a clean, structured way in order to quickly drive ROI.”
Collibra Announces New Innovations to Simplify and Scale Data Intelligence Across Organizations with Rich User Experiences
Collibra unveiled a wave of new innovations designed to make data intelligence easy and accessible to more data users with the performance, security, and scale that enterprise organizations demand. These innovations include new capabilities for Collibra Data Intelligence Cloud that enhance search, collaboration, business process automation, and analytics as well as brand new products that support customers with data access governance and data quality and observability in the cloud. Collibra Data Intelligence Cloud brings together an enterprise-grade data catalog, data lineage, flexible governance, continuous quality, and built-in data privacy.
“At Collibra we are building products and capabilities with an eye to making data intelligence easier for our customers — easier to get started, easier to use and manage, and easier to securely and cost-effectively scale to support even across the most demanding use cases,” said Laura Sellers, Chief Product Officer for Collibra. “We are incredibly excited about these new innovations because they make trusted data accessible to more users, across more use cases, and more data sources on a truly enterprise-grade, complete data intelligence platform.”
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