Best Data Management Software for Apache Parquet

StarfishETL is a Cloud iPaaS solution, which gives it the unique ability to connect virtually any kind of solution to any other kind of solution as long as both of those applications have an API. This gives StarfishETL customers ultimate control over their data projects, with the ability to build more unique and scalable data connections.

Connect your data to the Engine by uploading a file, or connecting to a database. You can then analyze your data with visualizations or prepare it for machine learning modeling using the data wrangling recipes. Build machine learning models using algorithms such as clustering, classification, or regression. All without writing any code. Discover insights into your data using the feature importance tools, prediction explanations, and what-ifs. Our connectors allow you to make predictions and integrate them into your existing systems.

Installed with one click, it's a desktop application that includes Jupyter Notebook. It has interactive code snippets, an AI assistant and a coding speed-up tool. Over 100 interactive code recipes have been handcrafted by us and can be used in Data Science projects. Code recipes detect the packages that are available in the current environment. Install modules with a single click. You can create variables and interact with them in your Python session. Interactive recipes speed-up your work. AI Assistant can access your current Python session and variables. It is smarter because it has a broad context. Our AI Assistant is designed to solve data issues using Python programming language. It can assist you with plots and data loading, data wrangling and Machine Learning. Click the Fix button to use AI to quickly fix code issues. The AI assistant will analyze and suggest a solution to the error.

Streamkap is a modern streaming ETL platform built on top of Apache Kafka and Flink, designed to replace batch ETL with streaming in minutes. It enables data movement with sub-second latency using change data capture for minimal impact on source databases and real-time updates. The platform offers dozens of pre-built, no-code source connectors, automated schema drift handling, updates, data normalization, and high-performance CDC for efficient and low-impact data movement. Streaming transformations power faster, cheaper, and richer data pipelines, supporting Python and SQL transformations for common use cases like hashing, masking, aggregations, joins, and unnesting JSON. Streamkap allows users to connect data sources and move data to target destinations with an automated, reliable, and scalable data movement platform. It supports a broad range of event and database sources.

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

Reframe your perception of time with data analytics. Instantly access the data of your business and work directly in your dashboard, without having to go back and forth with your IT team. Indexima DataHub is a new space where operational and functional users can instantly access their data. Indexima's unique indexing engine, combined with machine learning, allows businesses to quickly and easily access their data. The robust and scalable solution allows businesses to query their data directly from the source in volumes of up to tens billions of rows within milliseconds. With our Indexima platform, users can implement instant analytics for all their data with just one click. Indexima’s new ROI and TCO Calculator will help you determine the ROI of your data platform in just 30 seconds. Infrastructure costs, project deployment times, and data engineering cost, while boosting analytical performances.

PuppyGraph allows you to query multiple data stores in a single graph model. Graph databases can be expensive, require months of setup, and require a dedicated team. Traditional graph databases struggle to handle data beyond 100GB and can take hours to run queries with multiple hops. A separate graph database complicates architecture with fragile ETLs, and increases your total cost ownership (TCO). Connect to any data source, anywhere. Cross-cloud and cross region graph analytics. No ETLs are required, nor is data replication. PuppyGraph allows you to query data as a graph directly from your data lakes and warehouses. This eliminates the need for time-consuming ETL processes that are required with a traditional graph databases setup. No more data delays or failed ETL processes. PuppyGraph eliminates graph scaling issues by separating computation from storage.

Timeplus is an easy-to-use, powerful and cost-effective platform for stream processing. All in one binary, easily deployable anywhere. We help data teams in organizations of any size and industry process streaming data and historical data quickly, intuitively and efficiently. Lightweight, one binary, no dependencies. Streaming analytics and historical functionality from end-to-end. 1/10 of the cost of comparable open source frameworks Transform real-time data from the market and transactions into real-time insight. Monitor financial data using append-only streams or key-value streams. Implement real-time feature pipelines using Timeplus. All infrastructure logs, metrics and traces are consolidated on one platform. In Timeplus we support a variety of data sources through our web console UI. You can also push data using REST API or create external streams, without copying data to Timeplus.

Easy to capture, transform and load streaming data. Create a stream of data, select the destination and start streaming real time data in just a few simple clicks. Automate the provisioning and scaling of compute, memory and network resources, without any ongoing administration. Transform streaming data into formats such as Apache Parquet and dynamically partition streaming without building your own pipelines. Amazon Data Firehose is the fastest way to acquire data streams, transform them, and then deliver them to data lakes, warehouses, or analytics services. Amazon Data Firehose requires you to create a stream that includes a destination, a source and the transformations required. Amazon Data Firehose continuously processes a stream, scales automatically based on data availability, and delivers the results within seconds. Select the source of your data stream, or write data with the Firehose Direct PUT (API) API.

QStudio, a modern, free SQL editor, supports over 30 databases including MySQL, PostgreSQL and DuckDB. It has features like server browsing, which allows you to view tables, variables, functions and configuration settings. It also offers code completion, SQL syntax highlighting, the ability to query servers from the editor, and built-in charts that allow data visualization. QStudio is available on Windows, Mac and Linux. It offers excellent support for kdb+ and Parquet. Data pivoting, similar to Excel, is also available, as well as exporting data to Excel and CSV. AI-powered tools such as Text2SQL, which generates queries from plain English and Explain-My Query, for code walkthroughs and Explain-My Error, for debugging, are also available. Send the query and choose the chart type you want to create a chart. Send queries directly from the editor to your servers. All data structures are handled perfectly.

Mage Sensitive Data Discovery module can help you uncover hidden data locations in your company. You can find data hidden in any type of data store, whether it is structured, unstructured or Big Data. Natural Language Processing and Artificial Intelligence can be used to find data in the most difficult of places. A patented approach to data discovery ensures efficient identification of sensitive data and minimal false positives. You can add data classifications to your existing 70+ data classifications that cover all popular PII/PHI data. A simplified discovery process allows you to schedule sample, full, and even incremental scans.

Gravity's mission, to make streaming data from over 100 sources easy and only pay for what you use, is Gravity. Gravity eliminates the need for engineering teams to deliver streaming pipelines. It provides a simple interface that allows streaming to be set up in minutes using event data, databases, and APIs. All members of the data team can now create with a simple point-and-click interface so you can concentrate on building apps, services, and customer experiences. For quick diagnosis and resolution, full Execution trace and detailed error messages are available. We have created new, feature-rich methods to help you quickly get started. You can set up bulk, default schemas, and select data to access different job modes and statuses. Our intelligent engine will keep your pipelines running, so you spend less time managing infrastructure and more time analysing it. Gravity integrates into your systems for notifications, orchestration, and orchestration.

Meltano offers the most flexibility in deployment options. You control your data stack from beginning to end. Since years, a growing number of connectors has been in production. You can run workflows in isolated environments and execute end-to-end testing. You can also version control everything. Open source gives you the power and flexibility to create your ideal data stack. You can easily define your entire project in code and work confidently with your team. The Meltano CLI allows you to quickly create your project and make it easy to replicate data. Meltano was designed to be the most efficient way to run dbt and manage your transformations. Your entire data stack can be defined in your project. This makes it easy to deploy it to production.

Semarchy's flexible, unified data platform will help you make better business decisions across your organization. xDI is the high-performance, flexible, extensible data integration that integrates all your data for all types and uses. Its single technology can federate all forms of data integration and maps business rules into executable code. xDI supports multi-cloud environments, on-premise, hybrid, and cloud environments.

Apache Hadoop is a software library that allows distributed processing of large data sets across multiple computers. It uses simple programming models. It can scale from one server to thousands of machines and offer local computations and storage. Instead of relying on hardware to provide high-availability, it is designed to detect and manage failures at the application layer. This allows for highly-available services on top of a cluster computers that may be susceptible to failures.

IBM Db2 Events Store is a cloud-native database that can handle large amounts of structured data stored in Apache Parquet format. This high-speed data store is optimized for event-driven data processing. It can store, analyze, and store more that 250 billion events per day. The data store can be adapted quickly to meet changing business requirements. These data stores can be created in your Cloud Pak For Data cluster using the Db2 Events Store service. This allows you to manage the data and perform more detailed analysis. It is necessary to quickly ingest large amounts streaming data (upto one million inserts per minute per node) and use it to perform real-time analytics with integrated machine-learning capabilities. Analyze the incoming data from medical devices in real-time to improve patient health and reduce costs for storage.

Jump to our product page for more information about our data integration software. This includes solutions for Active Directory and SharePoint. Our data integration solutions offer developers the opportunity to use the flexibility and power offered by the SSIS ETL engine to connect almost any application or data source. Data integration is possible without writing any code. This means that your development can be completed in minutes. Our integration solutions are the most flexible on the market. Our software has intuitive user interfaces that make it easy and flexible to use. Our solution is easy to use and offers the best return on your investment. Our software has many features that will help you achieve the highest performance without consuming too much of your budget.

Amazon SageMaker Data Wrangler cuts down the time it takes for data preparation and aggregation for machine learning (ML). This reduces the time taken from weeks to minutes. SageMaker Data Wrangler makes it easy to simplify the process of data preparation. It also allows you to complete every step of the data preparation workflow (including data exploration, cleansing, visualization, and scaling) using a single visual interface. SQL can be used to quickly select the data you need from a variety of data sources. The Data Quality and Insights Report can be used to automatically check data quality and detect anomalies such as duplicate rows or target leakage. SageMaker Data Wrangler has over 300 built-in data transforms that allow you to quickly transform data without having to write any code. After you've completed your data preparation workflow you can scale it up to your full datasets with SageMaker data processing jobs. You can also train, tune and deploy models using SageMaker data processing jobs.

Data is used to inform every aspect of a plant or facility. It is the basis for most operational processes, business decisions, and environmental events. This data is often blamed for failures, whether it's operator error, bad sensor, safety or environmental events or poor analytics. APERIO can help solve these problems. Data integrity is a critical element of Industry 4.0. It is the foundation on which more advanced applications such as predictive models and process optimization are built. APERIO DataWise provides reliable, trusted data. Automate the quality of PI data and digital twins at scale. Validated data is required across the enterprise in order to improve asset reliability. Empowering the operator to take better decisions. Detect threats to operational data in order to ensure operational resilience. Monitor & report sustainability metrics accurately.

Scale from 0 to millions of events every second. Arroyo is shipped as a single compact binary. Run locally on MacOS, Linux or Kubernetes for development and deploy to production using Docker or Kubernetes. Arroyo is an entirely new stream processing engine that was built from the ground-up to make real time easier than batch. Arroyo has been designed so that anyone with SQL knowledge can build reliable, efficient and correct streaming pipelines. Data scientists and engineers are able to build real-time dashboards, models, and applications from end-to-end without the need for a separate streaming expert team. SQL allows you to transform, filter, aggregate and join data streams with results that are sub-second. Your streaming pipelines should not page someone because Kubernetes rescheduled your pods. Arroyo can run in a modern, elastic cloud environment, from simple container runtimes such as Fargate, to large, distributed deployments using the Kubernetes logo.

Limited competition due to high barriers to entry, specialized knowledge, massive capital requirements, and long times to market. The price and performance of existing platforms are virtually identical, reducing the incentive for a switch. It takes months to migrate from one engine's SQL dialect into another engine's SQL. Interoperable with all major standards. Data leaders in enterprise are being hit by a massive surge in computing demand. They are surprised to discover that 10% of heavy, compute-intensive uses cases consume 80% the cost, engineering efforts and stakeholder complaints. Unfortunately, these workloads are mission-critical and nondiscretionary. e6data increases ROI for enterprises' existing data platforms. e6data’s format-neutral computing is unique in that it is equally efficient and performant for all leading data lakehouse formats.

As a leader in business, you must be able to trust your data, and be 100 percent certain that they are accurate, well-governed and compliant. Include all data from all sources and all locations without limitation. Understanding your data assets. Audit your project for quality, compliance and risk. Catalogue a complete inventory of data across all data types and sources, creating a shared understanding about your data assets. Conduct a fast, accurate, and affordable audit of your data. PCI, PII and PHI audits can be completed quickly, accurately and completely. No software to buy, as a service. Measure and audit the data quality and duplication of data across all your enterprise data assets - cloud-native or on-premises. Ensure compliance with global data privacy laws at scale. Discover, classify and audit privacy compliance. Monitor PII/PCI/PHI and automate DSAR processes.

The smart semantic layer unifies metrics and speeds up the delivery of data products by 90% with shorter SQL queries. Model data using business terms for a common meaning and to align business metrics. Define semantic relationships to replace JOINs, making queries much easier. Hierarchies and classifications can help you better understand data. Automatically map data into the semantic model. Join multiple data sources using a powerful SQL engine distributed to query data at a large scale. Consume data in the form of a semantically connected graph. Materialized views and an intelligent cache engine can boost performance and reduce compute costs. Advanced query optimizations are available. Connect to any file format, cloud, datalake, data warehouse, or database. Timbr allows you to work seamlessly with your data sources. Timbr optimizes a query and pushes it to the backend when a query is executed.

Data contracts facilitate communication among data teams and developers. Don't only detect problematic changes; prevent them at the level of the application. AI-based asset tracking can detect every change from any data source. Drive adoption of data initiatives through upstream visibility and impact analyses. Data governance is a way to shift both ownership and management of data away from the user. Build data trust by communicating data quality expectations, changes and timely updates. Integrate our AI-driven technology to eliminate data issues at their source. You will find everything you need to ensure your data initiative is a success. Gable is an B2B SaaS data infrastructure that provides a collaborative platform to author and enforce contracts. Data contracts are API-based agreements that are made between software engineers who own the upstream data sources, and data engineers/analysts who consume data for machine learning models and analytics.

Protect, Monitor, and Discover enterprise sensitive data across multiple platforms and environments. Automate your subject rights response and demonstrate regulatory compliance - all in one solution