Business Software for Apache Avro

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.

Hackolade Studio is a powerful data modeling platform that supports a wide range of technologies including relational SQL and NoSQL databases, cloud data warehouses, APIs, streaming platforms, and data exchange formats. Designed for modern data architecture, it enables users to visually design, document, and evolve schemas across systems like Oracle, PostgreSQL, Databricks, Snowflake, MongoDB, Cassandra, DynamoDB, Neo4j, Kafka (with Confluent Schema Registry), OpenAPI, GraphQL, and more. Hackolade Studio offers forward and reverse engineering, schema versioning, model validation, and integration with metadata catalogs such as Unity Catalog and Collibra. It empowers data architects, engineers, and governance teams to collaborate on consistent, governed, and scalable data models. Whether building data products, managing API contracts, or ensuring regulatory compliance, Hackolade Studio streamlines the process in one unified interface.

Stop wasting time provisioning and maintaining databases yourself. Effortlessly create isolated test databases to ship features faster. Equip your developers with the ready-to-go data they need to keep fast-paced projects on track. Spin up pre-populated databases for testing purposes as part of your CI/CD pipeline, and automatically tear them down once the tests are done. Quickly and painlessly spin up databases at the click of a button for testing, bug reproduction, demos, and more with built-in container orchestration. Use our patented subsetter to shrink PBs down to GBs without breaking referential integrity, then leverage Tonic Ephemeral to spin up a database with only the data needed for development to cut cloud costs and maximize efficiency. Pair our patented subsetted with Tonic Ephemeral to get all the data subsets you need for only as long as you need them. Maximize efficiency by getting your developers access to one-off datasets for local development.

Timeplus is a simple, powerful, and cost-efficient stream processing platform. All in a single binary, easily deployed anywhere. We help data teams process streaming and historical data quickly and intuitively, in organizations of all sizes and industries. Lightweight, single binary, without dependencies. End-to-end analytic streaming and historical functionalities. 1/10 the cost of similar open source frameworks. Turn real-time market and transaction data into real-time insights. Leverage append-only streams and key-value streams to monitor financial data. Implement real-time feature pipelines using Timeplus. One platform for all infrastructure logs, metrics, and traces, the three pillars supporting observability. In Timeplus, we support a wide range of data sources in our web console UI. You can also push data via REST API, or create external streams without copying data into Timeplus.

Apache DataFusion is an extensible, high-performance query engine written in Rust that utilizes Apache Arrow as its in-memory format. Designed for developers building data-centric systems such as databases, data frames, machine learning, and streaming applications, DataFusion offers SQL and DataFrame APIs, a vectorized, multi-threaded, streaming execution engine, and support for partitioned data sources. It natively supports formats like CSV, Parquet, JSON, and Avro, and allows for seamless integration with object stores including AWS S3, Azure Blob Storage, and Google Cloud Storage. The engine features a comprehensive query planner, a state-of-the-art optimizer with capabilities like expression coercion and simplification, projection and filter pushdown, sort and distribution-aware optimizations, and automatic join reordering. DataFusion is highly customizable, enabling the addition of user-defined scalar, aggregate, and window functions, custom data sources, query languages, etc.

Beats is a free and open platform for single-purpose data shippers. They send data from hundreds or thousands of machines and systems to Logstash or Elasticsearch. Beats are open source data shippers that you install as agents on your servers to send operational data to Elasticsearch. Elastic provides Beats for capturing data and event logs. Beats can send data directly to Elasticsearch or via Logstash, where you can further process and enhance the data, before visualizing it in Kibana. Want to get up and running quickly with infrastructure metrics monitoring and centralized log analytics? Try out the Metrics app and the Logs app in Kibana. For more details, see Analyze metrics and Monitor logs. Whether you’re collecting from security devices, cloud, containers, hosts, or OT, Filebeat helps you keep the simple things simple by offering a lightweight way to forward and centralize logs and files.

Warp 10 is a modular open source platform that collects, stores, and analyzes data from sensors. 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 is both a time series database and a powerful analytics environment, allowing 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 analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system.

Experience Semarchy’s flexible unified data platform to empower better business decisions enterprise-wide. Integrate all your data with xDI, the high-performance, agile, and extensible data integration for all styles and use cases. Its single technology federates all forms of data integration, and mapping converts business rules into deployable code. xDI has extensible and open architecture supporting on-premise, cloud, hybrid, and multi-cloud environments.

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.

Limited competition due to deep barriers to entry, specialized know-how, massive capital needs, and long time-to-market. Existing platforms are indistinguishable in price, and performance reducing the incentive to switch. Migrating from one engine’s SQL dialect to another engine’s SQL involves months of effort. Truly format-neutral computing, interoperable with all major open standards. Enterprise data leaders are hit by an unprecedented explosion in computing demand for data intelligence. They are surprised to find that 10% of their heavy, compute-intensive use cases consume 80% of the cost, engineering effort and stakeholder complaints. Unfortunately, such workloads are also mission-critical and non-discretionary. e6data amplifies ROI on enterprises' existing data platforms and architecture. e6data’s truly format-neutral compute has the unique distinction of being equally efficient and performant across leading data lakehouse table formats.

Jump right to our product page to see our full range of data integration software, including solutions for SharePoint and Active Directory. With over 300 individual data integration tools for connectivity and productivity, our data integration solutions allow developers to take advantage of the flexibility and power of the SSIS ETL engine to integrate virtually any application or data source. You don't have to write a single line of code to make data integration happen so your development can be done in a matter of minutes. We make the most flexible integration solution on the market. Our software offers intuitive user interfaces that are flexible and easy to use. With a streamlined development experience and an extremely simple licensing model, our solution offers the best value for your investment. Our software offers many specifically designed features that help you achieve the best possible performance without having to hijack your budget.

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.