Apache NiFi Alternatives

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. • Gain critical real-time insights to run your business • Seamlessly integrate data streaming and batch data • High performance in throughput and low-latency at petabyte scale • Fully-managed cloud service • Tiered storage to optimize cloud performance & spend • Fully-secure & enterprise-ready

Voracity is the only high-performance, all-in-one data management platform accelerating AND consolidating the key activities of data discovery, integration, migration, governance, and analytics. Voracity helps you control your data in every stage of the lifecycle, and extract maximum value from it. Only in Voracity can you: 1) CLASSIFY, profile and diagram enterprise data sources 2) Speed or LEAVE legacy sort and ETL tools 3) MIGRATE data to modernize and WRANGLE data to analyze 4) FIND PII everywhere and consistently MASK it for referential integrity 5) Score re-ID risk and ANONYMIZE quasi-identifiers 6) Create and manage DB subsets or intelligently synthesize TEST data 7) Package, protect and provision BIG data 8) Validate, scrub, enrich and unify data to improve its QUALITY 9) Manage metadata and MASTER data. Use Voracity to comply with data privacy laws, de-muck and govern the data lake, improve the reliability of your analytics, and create safe, smart test data

Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.

The easiest way to do batch and streaming data processing. Write once, run anywhere data processing for mission-critical production workloads. Beam reads your data from a diverse set of supported sources, no matter if it’s on-prem or in the cloud. Beam executes your business logic for both batch and streaming use cases. Beam writes the results of your data processing logic to the most popular data sinks in the industry. A simplified, single programming model for both batch and streaming use cases for every member of your data and application teams. Apache Beam is extensible, with projects such as TensorFlow Extended and Apache Hop built on top of Apache Beam. Execute pipelines on multiple execution environments (runners), providing flexibility and avoiding lock-in. Open, community-based development and support to help evolve your application and meet the needs of your specific use cases.

A distributed data integration framework that simplifies common aspects of Big Data integration such as data ingestion, replication, organization, and lifecycle management for both streaming and batch data ecosystems. Runs as a standalone application on a single box. Also supports embedded mode. Runs as an mapreduce application on multiple Hadoop versions. Also supports Azkaban for launching mapreduce jobs. Runs as a standalone cluster with primary and worker nodes. This mode supports high availability and can run on bare metals as well. Runs as an elastic cluster on public cloud. This mode supports high availability. Gobblin as it exists today is a framework that can be used to build different data integration applications like ingest, replication, etc. Each of these applications is typically configured as a separate job and executed through a scheduler like Azkaban.

Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.

Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use! Apache Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Apache Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Apache Storm integrates with the queueing and database technologies you already use. An Apache Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed. Read more in the tutorial.

AppScope is a new approach to black-box instrumentation delivering ubiquitous, unified telemetry from any Linux executable by simply prepending scope to the command. Talk to any customer using Application Performance Management, and they’ll tell you how much they love their solution, but they wish they could extend it to more of their applications. Most have 10% or fewer of their apps instrumented for APM, and are supplementing what they can with basic metrics. Where does this leave the other 80%? Enter AppScope. No language-specific instrumentation. No application developers required. AppScope is language agnostic and completely userland; works with any application; scales from the CLI to production. Send AppScope data to any existing monitoring tool, time series database, or log tool. AppScope allows SREs and Ops teams to interrogate running applications to discover how they work and their behavior in any deployment context, from on-prem to cloud to containers.

Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers.

StreamSets DataOps Platform. The data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power modern analytics and hybrid integration. Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps. With StreamSets, you can deliver the continuous data that drives the connected enterprise.

Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi ​​that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes.

Samza allows you to build stateful applications that process data in real-time from multiple sources including Apache Kafka. Battle-tested at scale, it supports flexible deployment options to run on YARN or as a standalone library. Samza provides extremely low latencies and high throughput to analyze your data instantly. Scales to several terabytes of state with features like incremental checkpoints and host-affinity. Samza is easy to operate with flexible deployment options - YARN, Kubernetes or standalone. Ability to run the same code to process both batch and streaming data. Integrates with several sources including Kafka, HDFS, AWS Kinesis, Azure Eventhubs, K-V stores and ElasticSearch.

Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization.

Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.

Memgraph offers a light and powerful graph platform comprising the Memgraph Graph Database, MAGE Library, and Memgraph Lab Visualization. Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It comes with a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis, making Memgraph an excellent choice in critical decision-making scenarios such as risk assessment (fraud detection, cybersecurity threat analysis, and criminal risk assessment), 360-degree data and network exploration (Identity and Access Management (IAM), Master Data Management (MDM), Bill of Materials (BOM)), and logistics and network optimization.

Baidu Stream Computing (BSC) provides real-time streaming data processing capacity with low delay, high throughput and high accuracy. It is fully compatible with Spark SQL; and can realize the logic data processing of complicated businesses through SQL statement, which is easy to use; provides users with full life cycle management for the streaming-oriented computing jobs. Integrate deeply with multiple storage products of Baidu AI Cloud as the upstream and downstream of stream computing, including Baidu Kafka, RDS, BOS, IOT Hub, Baidu ElasticSearch, TSDB, SCS and others. Provide a comprehensive job monitoring indicator, and the user can view the monitoring indicators of the job and set the alarm rules to protect the job.

Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault-tolerant with tunable reliability mechanisms and many failovers and recovery mechanisms. It uses a simple extensible data model that allows for online analytic applications. The Apache Flume team is pleased to announce the release of Flume 1.8.0. Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming event data.

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

Nussknacker is a low-code visual tool for domain experts to define and run real-time decisioning algorithms instead of implementing them in the code. It serves where real-time actions on data have to be made: real-time marketing, fraud detection, Internet of Things, Customer 360, and Machine Learning inferring. An essential part of Nussknacker is a visual design tool for decision algorithms. It allows not-so-technical users – analysts or business people – to define decision logic in an imperative, easy-to-follow, and understandable way. Once authored, with a click of a button, scenarios are deployed for execution. And can be changed and redeployed anytime there’s a need. Nussknacker supports two processing modes: streaming and request-response. In streaming mode, it uses Kafka as its primary interface. It supports both stateful and stateless processing.

A holistic component-based platform for automating Data Reconciliation tests in modern Data Lake and Cloud Data Migration projects using Apache Spark. DataOps Dataflow is a modern, web browser-based solution for automating the testing of ETL, Data Warehouse, and Data Migration projects. Use Dataflow to inject data from any of the varied data sources, compare data, and load differences to S3 or a database. With fast and easy to set up, create and run dataflow in minutes. A best in the class testing tool for Big Data Testing DataOps Dataflow can integrate with all modern and advanced data sources including RDBMS, NoSQL, Cloud, and File-Based.

Responsive applications keep users engaged and developers inspired. Rise to meet these ever-increasing expectations with the DataStax Astra Streaming service platform. DataStax Astra Streaming is a cloud-native messaging and event streaming platform powered by Apache Pulsar. Astra Streaming allows you to build streaming applications on top of an elastically scalable, multi-cloud messaging and event streaming platform. Astra Streaming is powered by Apache Pulsar, the next-generation event streaming platform which provides a unified solution for streaming, queuing, pub/sub, and stream processing. Astra Streaming is a natural complement to Astra DB. Using Astra Streaming, existing Astra DB users can easily build real-time data pipelines into and out of their Astra DB instances. With Astra Streaming, avoid vendor lock-in and deploy on any of the major public clouds (AWS, GCP, Azure) compatible with open-source Apache Pulsar.

GS RichCopy 360 Folder Copying Suite is widely used in several fortune 500 companies in the United States and more than 10,000 customers worldwide. It has been viewed as the most robust copying software due to its unique pure multithreaded technology used where all the thread are evenly divided on all logical cores. Let alone its patent-pending simple and intuitive design and many key features it offers. You need to copy a large collection of files from one server location to another. It’s a task that should be so easy to implement – but you know how this simple task is littered with annoying frustrations. Locked open files initiate endless "File in Use" errors and no matter what time you attempt to run this task, there always seem to be filed in use. Copy operations continually fail, alerting you that the file path is too long and needs to be modified.

Built on open-source Apache Kafka, IBM® Event Streams is an event-streaming platform that helps you build smart apps that can react to events as they happen. Event Streams is based on years of IBM operational expertise gained from running Apache Kafka event streams for enterprises. This makes Event Streams ideal for mission-critical workloads. With connectors to a wide range of core systems and a scalable REST API, you can extend the reach of your existing enterprise assets. Rich security and geo-replication aids disaster recovery. Take advantage of IBM productivity tools and use the CLI to ensure best practices. Replicate data between Event Streams deployments in a disaster-recovery situation.

Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools.

Seamlessly extend your on-premises environments into cloud. VMware HCX streamlines application migration, workload rebalancing and business continuity across data centers and clouds. Large-scale movement of workloads across any VMware platform. vSphere 5.0+ to any current vSphere version on cloud or modern data center. KVM and Hyper-V conversion to any current vSphere version. Support for VMware Cloud Foundation, VMware Cloud on AWS, Azure VMware Services and more. Choice of migration methodologies to meet your workload needs. Live large-scale HCX vMotion migration of 1000’s of VMs. Zero downtime migration to limit business disruption. Secure proxy for vMotion and replication traffic. Migration planning and visibility dashboard. Automated migration-aware routing with NSX for network connectivity. WAN optimized links for migration across Internet or WAN. High-throughput L2 extension. Advanced traffic engineering to optimize the application migration times.

Streaming service is a real-time, serverless, Apache Kafka-compatible event streaming platform for developers and data scientists. Streaming is tightly integrated with Oracle Cloud Infrastructure (OCI), Database, GoldenGate, and Integration Cloud. The service also provides out-of-the-box integrations for hundreds of third-party products across categories such as DevOps, databases, big data, and SaaS applications. Data engineers can easily set up and operate big data pipelines. Oracle handles all infrastructure and platform management for event streaming, including provisioning, scaling, and security patching. With the help of consumer groups, Streaming can provide state management for thousands of consumers. This helps developers easily build applications at scale.

DeltaStream is a unified serverless stream processing platform that integrates with streaming storage services. Think about it as the compute layer on top of your streaming storage. It provides functionalities of streaming analytics(Stream processing) and streaming databases along with additional features to provide a complete platform to manage, process, secure and share streaming data. DeltaStream provides a SQL based interface where you can easily create stream processing applications such as streaming pipelines, materialized views, microservices and many more. It has a pluggable processing engine and currently uses Apache Flink as its primary stream processing engine. DeltaStream is more than just a query processing layer on top of Kafka or Kinesis. It brings relational database concepts to the data streaming world, including namespacing and role based access control enabling you to securely access, process and share your streaming data regardless of where they are stored.

Infinite retention for Apache Kafka® with Confluent. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming enables you to innovate and win - by being both real-time and highly-scalable. Ever wonder how your rideshare app analyzes massive amounts of data from multiple sources to calculate real-time ETA? Ever wonder how your credit card company analyzes millions of credit card transactions across the globe and sends fraud notifications in real-time? The answer is event streaming. Move to microservices. Enable your hybrid strategy through a persistent bridge to cloud. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. The list is endless.

Simplifies data exchange between components in microservice architectures. When used as a transport for microservices, it simplifies integration, increases reliability, and improves scaling. Read and write data in near real-time. Set data throughput and storage times to meet your needs. Enjoy granular configuration of the resources for processing data streams, from small streams of 100 KB/s to streams of 100 MB/s. Deliver a single stream to multiple targets with different retention policies using Yandex Data Transfer. Data is automatically replicated across multiple geographically distributed availability zones. Once created, you can manage data streams centrally in the management console or using the API. Yandex Data Streams can continuously collect data from sources like website browsing histories, application and system logs, and social media feeds. Yandex Data Streams is capable of continuously collecting data from sources such as website browsing histories, application logs, etc.

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.

Breakthrough data streaming capabilities that let you deliver customer experiences never before possible. Kafka API and ecosystem are compatible. Redpanda BulletPredictable low latencies with zero data loss. Redpanda BulletUpto 10x faster than Kafka. Redpanda BulletEnterprise-grade support and hotfixes. Redpanda BulletAutomated backups to S3/GCS. Redpanda Bullet100% freedom from routine Kafka operations. Redpanda BulletSupport for AWS and GCP. Redpanda was designed from the ground up to be easily installed to get streaming up and running quickly. After you see its power, put Redpanda to the test in production. Use the more advanced Redpanda features. We manage provisioning, monitoring, and upgrades. Without any access to your cloud credentials. Sensitive data never leaves your environment. Provisioned, operated, and maintained for you. Configurable instance types. Expand cluster as your needs grow.

SQLstream ranks #1 for IoT stream processing & analytics (ABI Research). Used by Verizon, Walmart, Cisco, & Amazon, our technology powers applications across data centers, the cloud, & the edge. Thanks to sub-ms latency, SQLstream enables live dashboards, time-critical alerts, & real-time action. Smart cities can optimize traffic light timing or reroute ambulances & fire trucks. Security systems can shut down hackers & fraudsters right away. AI / ML models, trained by streaming sensor data, can predict equipment failures. With lightning performance, up to 13M rows / sec / CPU core, companies have drastically reduced their footprint & cost. Our efficient, in-memory processing permits operations at the edge that are otherwise impossible. Acquire, prepare, analyze, & act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code GUI dev environment. Export SQL scripts & deploy with the flexibility of Kubernetes.

Easily collect, process, and analyze video and data streams in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin. Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days.

Query and shape your data using Pipes, a new way to chain SQL queries inspired by Python Notebooks. Designed to reduce complexity without sacrificing performance. By splitting your query in different nodes you simplify development and maintenance. Activate your production-ready API endpoints with one click. Transformations occur on-the-fly so you will always work with the latest data. Share access securely to your data in one click and get fast and consistent results. Apart from providing monitoring tools, Tinybird scales linearly: don't worry about traffic spikes. Imagine if you could turn, in a matter of minutes, any Data Stream or CSV file into a fully secured real-time analytics API endpoint. We believe in high-frequency decision-making for all organizations in all industries including retail, manufacturing, telecommunications, government, advertising, entertainment, healthcare, and financial services.

The RecordPoint Data Trust platform helps highly regulated organizations manage records and data throughout their lifecycle, regardless of system. The customizable platform is comprised of records management and data lineage tools that work together to give you full context of your data. RecordPoint’s capabilities span six core areas, which are the essential building blocks for solid data governance - data inventory, categorization, records management, privacy, minimization, and migration.

Design, debug, run and troubleshoot data transformations and jobflows in a developer-friendly visual designer. Orchestrate data workloads that require tasks to be carried out in the right sequence, orchestrate multiple systems with the transparency of visual workflows. Deploy data workloads easily into a robust enterprise runtime environment. In cloud or on-premise. Make data available to people, applications and storage under a single unified platform. Manage your data workloads and related processes together in a single platform. No task is too complex. We’ve built CloverDX on years of experience with large enterprise projects. Developer-friendly open architecture and flexibility lets you package and hide the complexity for non-technical users. Manage the entire lifecycle of a data pipeline from design, deployment to evolution and testing. Get things done fast with the help of our in-house customer success teams.

Oracle Forms Code Analysis Tool: Customized Oracle Forms/Reports application development brings high levels of flexibility but with years of code maintenance and modifications, your application code documentation is obsolete 90% of the time. Our state of the art Oracle validated ORMIT-Analyzer tool helps understand the existing development patterns and to find opportunities to simplify the source code. The objective is to obtain detailed information on the possibilities and challenges to enable a more “future-ready” software architecture by separating the software architectural components: User-Interface, Business Logic and Database. ORMIT-Analyzer also helps prepare a potential application modernization project with the objective to protect the investment in the existing business logic and to achieve easier maintainable, more modern software architecture.

Get a free report with a detailed analysis of your source code. Plus, a migration engineer will help you understand how to migrate your project. A quick phone call to review your data can provide valuable insights into what workloads can be made cloud-ready quickly, and which might need additional effort. VB6 has been out of support for over a decade. The Visual Basic Upgrade Companion quickly and efficiently migrates VB6 code to C# or VB.NET and .NET Core or Framework with Windows Forms. Faster than a rewrite, more productive than all other solutions. VBUC moves forms, business logic, and object names to .NET Framework or Core, keeping proven and debugged logic and processes intact. Web apps can be complex. WebMAP moves your .NET, PowerBuilder, and Winforms apps to the native web with Angular and ASP.NET Core while hiding the clutter.

Data Migration Manager (DMM) for OutSystems automates data & BPT migration, export, import, data deletion or scramble/anonymization between all OutSystems environments (Cloud, Onprem, PaaS, Hybrid, mySQL, Oracle, SQL Server, Azure SQL, Java or .NET) and versions (8, 9, 10 or 11). Only solution with FREE download directly from the OS FORGE! Did you... Upgrade servers, migrate apps but now you need to migrate the data & BPT or Light BPT? Need to migrate data from the Qual to Prod Environment to populate lookup data? Need to migrate from Prod to Qual to replicate situations that need fixing or just getting a good QA environment for testing? Need to backup data for later restore of a demo environment? Need to import data into OutSystems from other systems? Need to validate performance or do pen testing? What is Infosistema DMM? https://www.youtube.com/watch?v=strh2TLliNc Reduce costs, reduce risk, increase time-to-market! DMM is the fastest solution!

With Talend Open Studio, you can begin building basic data pipelines in no time. Execute simple ETL and data integration tasks, get graphical profiles of your data, and manage files — from a locally installed, open-source environment that you control. If your project is ready to go, jump right in with Talend Cloud. You get the same easy-to-use interface of Open Studio, plus the tools for collaboration, monitoring, and scheduling that ongoing projects require. You can easily add data quality, big data integration, and processing resources, and take advantage of the latest data sources, analytics technologies, and elastic capacity from AWS or Azure when you need it. Join the Talend Community and start your data integration journey on the right foot. Whether you’re a beginner or an expert, the Talend Community is the place to share best practices and hunt for new tricks you haven’t tried.

Businesses are moving their communication and collaboration systems to the cloud. They need an independent backup or archival of their data on a separate cloud to protect against vendor lock-in and downtime. Data operations with a high degree of human effort are prone to data loss or data theft. New tools need to support a large number of data types and also have strong in-built data integrity checks to enable error-free and quick migration of large volumes of data. Old software requires physical hardware to be provisioned and is also not geared to handle data generated by the new Saas tools. These tools require a very high degree of human effort to transform data. As the adoption of cloud communication services grows, huge volumes of data are generated. Operating on this data requires systems that are automated and highly scalable. Need hands-free and automation to ensure that the data being operated upon is secure.

SmartParse is a tool that simplifies data migration from any flat file to any API with minimal setup, offering a quick, low-code solution for integrating systems. With high scalability, it can manage files from a few rows to millions of lines.

GS RichCopy 360 is an enterprise grade-data migration software. It makes a copy of your data (files and folders) to another location. It has a multi-threading technology so that files are copied simultaneously. Copy to Office 365 OneDrive and SharePoint. Copy open files. Copy NTFS permissions. Support Long Path Name. Run according to a scheduler and as a service (you do not need to be logged in). Copy file and folder attributes and time stamps. Send an email when it is completed. Phone and email support. Easy to use. Copy using a single TCP port across the internet and have data encrypted while in-transit. Byte level replication (copy only the deltas in the file instead of the whole file). Superior and robust performance. Supports Windows 7 and later (Windows 8, Windows 8.1, Windows 10. Supports Windows Server 2008R2 and Later (Windows Server 2012, 2012R2, 2016, and 2019).

On-premises and cloud-based data migrations among nearly 20 types of data sources are supported. The distributed computing framework ensures high-performance data migration and optimal data writing of specific data sources. The wizard-based development interface frees you from complex programming and helps you quickly develop migration tasks. You only pay for what you use and do not need to build dedicated hardware and software. Big data cloud services can replace or back up on-premises big data platforms and support full migration of massive amounts of data. Support for relational databases, big data, files, NoSQL, and many other data sources ensures a wide application scope. Wizard-based task management provides out-of-the-box usability. Data is migrated between services on HUAWEI CLOUD, achieving data mobility.

Qlik Replicate (formerly Attunity Replicate) is a high-performance data replication tool offering optimized data ingestion from a broad array of data sources and platforms and seamless integration with all major big data analytics platforms. Replicate supports bulk replication as well as real-time incremental replication using CDC (change data capture). Our unique zero-footprint architecture eliminates unnecessary overhead on your mission-critical systems and facilitates zero-downtime data migrations and database upgrades. Database replication enables you to move or consolidate data from a production database to a newer version of the database, another type of computing environment, or an alternative database management system, to migrate data from SQL Server to Oracle, for example. Data replication can be used to offload production data from a database, and load it to operational data stores or data warehouses for reporting or analytics.

iCEDQ is a DataOps platform for testing and monitoring. iCEDQ is an agile rules engine for automated ETL Testing, Data Migration Testing, and Big Data Testing. It improves the productivity and shortens project timelines of testing data warehouse and ETL projects with powerful features. Identify data issues in your Data Warehouse, Big Data and Data Migration Projects. Use the iCEDQ platform to completely transform your ETL and Data Warehouse Testing landscape by automating it end to end by letting the user focus on analyzing and fixing the issues. The very first edition of iCEDQ designed to test and validate any volume of data using our in-memory engine. It supports complex validation with the help of SQL and Groovy. It is designed for high-performance Data Warehouse Testing. It scales based on the number of cores on the server and is 5X faster than the standard edition.

Our state-of-the-art data migration tool is specially designed to effectively convert and migrate data from outdated legacy applications to advanced systems and frameworks with advanced data validation mechanisms and real-time reporting. Too often in the data migration process, data is lost or corrupted. When transferring information from old legacy systems to new advanced systems, the process is complex and time-consuming. Cutting corners or attempting to integrate the data without the proper tools may seem appealing, but often results in costly and drawn-out exercises of frustration. For organizations such as State Agencies, the risk is simply too high, not to get it right the first time. This is the most challenging phase, and one many organizations fail to get right. A good data migration project is built on the foundation of the initial design. This is where you will design and hand-code the rules of the project to handle different data according to your specifications.

Ispirer SQLWays Toolkit is an easy-to-use cross-database migration tool. It allows to migrate the entire database schema, including SQL objects, tables and data from source to target databases. Smart conversion, teamwork, technical support, the tool customization according to your project requirements – all of these capabilities are combined in one solution. Customization option. The migration process using SQLWays Toolkit can be customized to tailor specific business needs. Essentially, it accelerates database modernization considerably. High level of automation. Smart migration core provides a high level of automation for the migration process, ensuring a consistent and reliable migration. Code security. Privacy is of utmost importance to us. That is why we developed the tool that does not save or send the code structures it processes. With our tool, you can be sure that your data is safe, since our tool can work even without an Internet connection.

MSSQL-to-PostgreSQL is a program to migrate databases from SQL Server and Azure SQL to PostgreSQL on-premises or cloud DBMS. The program has high performance due to low-level algorithms of reading and writing data: more than 10 MB per second on an average modern system. Command line support allows to automate the migration process.

MigrationPro is a Shopping Cart Migration service designed for e-commerce businesses, web agencies, and various online retailers effectively migrate their store data from one platform to another. The service provides compatibility with a diverse range of e-commerce platforms, including Shopify, BigCommerce, WooCommerce, Magento, and PrestaShop, ensuring adaptability to a broad spectrum of business requirements. By automating the complex data migration procedure, the tool ensures the precise transfer of vital store components, such as product information, customer details, and order histories. It places a high emphasis on maintaining operational continuity and data security during the transition, thus minimizing any potential disruptions to business activities while guaranteeing the integrity of the migrated data. MigrationPro offers a flexible pricing model corresponding to the specific data entities a user decides to transfer, catering to varying scalability needs.