Best Data Management Software for Python - Page 5

Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes.

Privacy-minded organizations work with Decentriq. With the latest advancements in encryption and privacy-enhancing technologies such as synthetic data, differential privacy, and confidential computing, your data stays under your control at all times. End-to-end encryption keeps your data private to all other parties. Decentriq cannot see or access your data. Remote attestation gives you verification that your data is encrypted and only approved analyses are running. Built-in partnership with market-leading hardware and infrastructure providers. Designed to handle even advanced AI and machine learning models, the platform keeps your data inaccessible no matter the challenge. With processing speeds approaching typical cloud levels, you don’t have to sacrifice scalability for excellent data protection. Our growing network of data connectors supports more streamlined workflows across leading data platforms.

We help businesses unlock the power of 1st party data collaboration without the risks. Transform your consumer data from a liability to a revenue-generating asset. Thrive in the post-cookie world with 1st party consumer data. Collaborate with more partners to unlock more value for your customers. Grow financial inclusion and increase revenue through innovative alternative data partners. Enhance underwriting accuracy and maximize profitability with alternative data sources. Each participating party uses our desktop application to anonymize, tokenize, and protect all personally identifiable information in their consumer data set within their own local environment. The process generates US-patented crypto-IDs for each anonymized consumer profile locally to enable the matching of mutual consumers across multiple data sets in our secure and neutral Cloud environment. We’re leading the next generation of consumer data.

Ultra-reliable SQL-standard transactional database with X100 operational analytics. Actian Ingres has long been known as an ultra-reliable enterprise transactional database. Today Actian Ingres is a hybrid transactional/analytical processing database with record-breaking performance. Ingres supports both row-based and columnar storage formats using its ultra-reliable enterprise transactional database, and Vector’s X100 analytics engine. This combination allows organizations to perform transaction processing and operational analytics easily and efficiently within a single database. The most trusted and time-tested transactional database with a low total cost of ownership, 24/7 global support, and industry-leading customer satisfaction. It has a proven track record, with thousands of enterprises running billions of transactions over decades of deployment, upgrades, and migrations.

All your data needs are delivered in one powerful platform. From data ingestion/integration, transformation, and storage to knowledge catalog, graph networks, data analytics, governance, monitoring, and, sharing. ​ An AI/ML platform that lets enterprises, train, test, troubleshoot, deploy, and govern models at scale to boost productivity while maintaining model performance in production with confidence. A dedicated solution for training models with minimal effort through AutoML or training your case-specific models from scratch with CustomML. Giving you the power to connect essential logic from ML with data. An integrated exploration of possible actions.​ Integration with your protocols and authorization models​. Propagation by default; extreme configurability at your service​. Leverage internal lineage system, for alerting and impact analysis​. Interwoven with the security paradigm; provides immutable tracking​.

The smart semantic layer integrates data with business meaning and relationships, unifies metrics, and accelerates the delivery of data products with 90% shorter SQL queries. Easily model data using business terms to give it common meaning and align business metrics. Define semantic relationships that substitute JOINs so queries become much simpler. Use hierarchies and classifications to better understand data. Automatically map data to the semantic model. Join multiple data sources with a powerful distributed SQL engine to query data at scale. Consume data as a connected semantic graph. Boost performance and save compute costs with an intelligent cache engine and materialized views. Benefit from advanced query optimizations. Connect to most clouds, datalakes, data warehouses, databases, and any file format. Timbr empowers you to work with your data sources seamlessly. When a query is run, Timbr optimizes the query and pushes it down to the backend.

Common dashboards, reporting, and ETL tools often lack connectivity to certain data sources, creating integration challenges for users. Simba offers ready-to-use, standards-based drivers that ensure compatibility, simplifying the connectivity process. Companies that provide data to customers struggle to offer headache-free, easy data connectivity to their users. Simba’s SDK allows developers to build custom, standards-based drivers, making connectivity more friendly than CSV export or API-based access. Unique backend requirements, such as specific implementation needs dictated by specific applications or internal processes, can complicate connectivity. Using Simba’s SDK or managed services enables the creation of drivers tailored to meet these requirements. Simba provides comprehensive ODBC/JDBC extensibility for a wide range of applications and data tools. Simba Drivers plug into these tools to enhance their offerings, enabling additional connectivity to data sources.

Data contracts facilitate communication between data teams and developers. Don’t just detect problematic changes, prevent them at the application level. Detect every change, from every data source using AI-based asset registration. Drive the adoption of data initiatives with upstream visibility and impact analysis. Shift left both data ownership and management through data governance as code and data contracts. Build data trust through the timely communication of data quality expectations and changes. Eliminate data issues at the source by seamlessly integrating our AI-driven technology. Everything you need to make your data initiative a success. Gable is a B2B data infrastructure SaaS that provides a collaboration platform to author and enforce data contracts. ‘Data contracts’, refer to API-based agreements between the software engineers who own upstream data sources and data engineers/analysts that consume data to build machine learning models and analytics.

Invert offers a complete suite for collecting, cleaning, and contextualizing data, ensuring every analysis and insight is based on reliable, organized data. Invert collects and standardizes all your bioprocess data, with powerful, built-in products for analysis, machine learning, and modeling. Clean, standardized data is just the beginning. Explore our suite of data management, analysis, and modeling tools. Replace manual workflows in spreadsheets or statistical software. Calculate anything using powerful statistical features. Automatically generate reports based on recent runs. Add interactive plots, calculations, and comments and share with internal or external collaborators. Streamline planning, coordination, and execution of experiments. Easily find the data you need, and deep dive into any analysis you'd like. From integration to analysis to modeling, find all the tools you need to manage and make sense of your data.

Oracle NoSQL Database is designed to handle high-volume, high-velocity data applications requiring low-latency responses and flexible data models. It supports JSON, table, and key-value data types, and operates both on-premise and as a cloud service. The database scales elastically to meet dynamic workloads and provides distributed data storage across multiple shards, ensuring high availability and rapid failover. It includes Python, Node.js, Java, C, C#, and REST API drivers for easy application development. Additionally, it integrates with Oracle products such as IoT, Golden Gate, and Fusion Middleware. Oracle NoSQL Database Cloud Service is a fully managed service, freeing developers from backend infrastructure management. Oracle NoSQL Database Cloud Service is a fully managed database service for developers who want to focus on application development without dealing with the hassle of managing the back-end hardware and software infrastructure.

Nextdata is a data mesh operating system designed to decentralize data management, enabling organizations to create, share, and manage data products across various data stacks and formats. By encapsulating data, metadata, code, and policies into portable containers, it simplifies the data supply chain, ensuring data is useful, safe, and discoverable. Automated policy enforcement is embedded as code, continuously evaluating and maintaining data quality and compliance. The system integrates seamlessly with existing data infrastructures, allowing configuration and provisioning of data products as needed. It supports processing data from any source in any format, facilitating analytics, machine learning, and generative AI applications. Nextdata automatically generates and synchronizes real-time metadata and semantic models throughout the data product's lifecycle, enhancing discoverability and usability.

TROCCO is a fully managed modern data platform that enables users to integrate, transform, orchestrate, and manage their data from a single interface. It supports a wide range of connectors, including advertising platforms like Google Ads and Facebook Ads, cloud services such as AWS Cost Explorer and Google Analytics 4, various databases like MySQL and PostgreSQL, and data warehouses including Amazon Redshift and Google BigQuery. The platform offers features like Managed ETL, which allows for bulk importing of data sources and centralized ETL configuration management, eliminating the need to manually create ETL configurations individually. Additionally, TROCCO provides a data catalog that automatically retrieves metadata from data analysis infrastructure, generating a comprehensive catalog to promote data utilization. Users can also define workflows to create a series of tasks, setting the order and combination to streamline data processing.

Betteromics is deployed as a Private SaaS in your VPC so you can draw connections on all your data. Reproducibly validate your structured and unstructured data using configurable rules. Trace and audit your data from input to analysis with complete data provenance. Use natural language processing and large language models to abstract data elements from clinical records for QC, labeling, and analysis. Quickly develop and tune models specific to your task/data: detect anomalies, make predictions, understand your data, and optimize your processes. Enhance and complement your analysis and machine learning with integration-ready public datasets. Clinical-grade security including full encryption, data traceability, and role-based access controls.

Coactive supercharges data-driven businesses. We bring structure to unstructured data and help analysts to make image and video data useful. Bringing unprecedented insights, ease of use, and blistering speeds, we can make machine learning your new superpower. Don't waste your time flipping through photos or scrubbing through videos. With a word or phrase, you can search your content library and refine the taxonomy of your content. Your data is constantly evolving, and Coactive is here to help. Use our API and Python SDKs to understand and monitor your data as it's coming in. Coactive is prioritizing integrity alongside sales in a way that will ultimately benefit both the company and customers. Coactive AI is an industry-leading machine learning platform that enables businesses of all sizes to analyze their unstructured image data in minutes. Our interface is clean, intuitive, and user-friendly, and our platform is blisteringly fast.

IBM SPSS Modeler is a leading visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations worldwide use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets. IBM SPSS Modeler automatically transforms data into the best format for the most accurate predictive modeling. It now only takes a few clicks for you to analyze data, identify fixes, screen out fields and derive new attributes. Leverage IBM SPSS Modeler’s powerful graphics engine to bring your insights to life. The smart chart recommender finds the perfect chart for your data from among dozens of options, so you can share your insights quickly and easily using compelling visualizations.

Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster.

As a business leader, you need to trust your data and be 100% certain that it’s well-governed, compliant, and accurate. Including all data, in all sources, and in all locations, without limitations. Understand your data assets. Audit for risk, compliance, and quality in support of your project. Catalog a complete data inventory across all sources and data types, creating a shared understanding of your data assets. Run a one-time, fast, affordable, and accurate audit of your data. PCI, PII, and PHI audits are fast, accurate, and complete. As a service, with no software to purchase. Measure and audit data quality and data duplication across all of your enterprise data assets, cloud-native and on-premises. Comply with global data privacy regulations at scale. Discover, classify, track, trace and audit privacy compliance. Monitor PII/PCI/PHI data propagation and automate DSAR compliance processes.

TopK is a serverless, cloud-native, document database built for powering search applications. It features native support for both vector search (vectors are simply another data type) and keyword search (BM25-style) in a single, unified system. With its powerful query expression language, TopK enables you to build reliable search applications (semantic search, RAG, multi-modal, you name it) without juggling multiple databases or services. Our unified retrieval engine will evolve to support document transformation (automatically generate embeddings), query understanding (parse metadata filters from user query), and adaptive ranking (provide more relevant results by sending “relevance feedback” back to TopK) under one unified roof.

Row Zero is the best spreadsheet for big data. Row Zero matches the experience of traditional spreadsheets but can handle 1+ billion rows, process data much faster, and connect live to your data warehouse and other data sources. Row Zero spreadsheets are powerful enough to pull entire database tables into a spreadsheet, letting non-technical users build live pivot tables, graphs, models, and metrics on data from your data warehouse. Row Zero also offers advanced security features and is cloud-based, empowering organizations to eliminate ungoverned CSV exports and locally stored spreadsheets from their org. With Row Zero, you can easily open, edit, and share multi-GB files (CSV, parquet, txt, etc.) Row Zero has all of the spreadsheet features you know and love, but was built for big data. If you know how to use Excel or Google Sheets, you can get started with ease.

Our web scraping API handles all problems that are related to web scraping. Website HTML extraction has never been so easy! Response times are everything. Our API is among the fastest you will find in the industry. Our API always provides enough performance, no matter how many requests you submit. Chances are high that you are not alone with your use case. Join our customer family. We believe in fair pricing. Hence, we offer you 1000 API requests pers month for free. No strings attached! Getting started is easy. We provide an extensive request builder, that converts your requests into production ready code snippets. Zenscrape can be used with any programming language, as data can be simply retrieved by any HTTP client.