Alternatives to Apache NiFi

Airflow is a community-created platform that allows programmatically to schedule, author, and monitor workflows. Airflow is modular in architecture and uses a message queue for managing a large number of workers. Airflow can scale to infinity. Airflow pipelines can be defined in Python to allow for dynamic pipeline generation. This allows you to write code that dynamically creates pipelines. You can easily define your own operators, and extend libraries to suit your environment. Airflow pipelines can be both explicit and lean. The Jinja templating engine is used to create parametrization in the core of Airflow pipelines. No more XML or command-line black-magic! You can use standard Python features to create your workflows. This includes date time formats for scheduling, loops to dynamically generate task tasks, and loops for scheduling. This allows you to be flexible when creating your workflows.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

A distributed data integration framework which simplifies common Big Data integration tasks such as data ingestion and replication, organization, and lifecycle management. It can be used for both streaming and batch data ecosystems. It can be run as a standalone program on a single computer. Also supports embedded mode. It can be used as a mapreduce application on multiple Hadoop versions. Azkaban is also available for the launch of mapreduce jobs. It can run as a standalone cluster, with primary and worker nodes. This mode supports high availability, and can also run on bare metals. This mode can be used as an elastic cluster in the public cloud. This mode supports high availability. Gobblin, as it exists today, is a framework that can build various data integration applications such as replication, ingest, and so on. Each of these applications are typically set up as a job and executed by Azkaban, a scheduler.

This is the easiest way to perform batch and streaming data processing. For mission-critical production workloads, write once and run anywhere data processing. Beam can read your data from any supported source, whether it's on-prem and in the cloud. Beam executes your business logic in both batch and streaming scenarios. Beam converts the results of your data processing logic into the most popular data sinks. A single programming model that can be used for both streaming and batch use cases. This is a simplified version of the code for all members of your data and applications teams. Apache Beam is extensible. TensorFlow Extended, Apache Hop and other projects built on Apache Beam are examples of Apache Beam's extensibility. Execute pipelines in multiple execution environments (runners), allowing flexibility and avoiding lock-in. Open, community-based development and support are available to help you develop your application and meet your specific needs.

Apache Storm is an open-source distributed realtime computing system that is free and open-source. Apache Storm makes it simple to process unbounded streams and data reliably, much like Hadoop did for batch processing. Apache Storm is easy to use with any programming language and is a lot fun! Apache Storm can be used for many purposes: realtime analytics and online machine learning. It can also be used with any programming language. Apache Storm is fast. A benchmark measured it at more than a million tuples per second per node. It is highly scalable, fault-tolerant and guarantees that your data will be processed. It is also easy to set up. Apache Storm can be integrated with the queueing and databases technologies you already use. Apache Storm topology processes streams of data in arbitrarily complex ways. It also partitions the streams between each stage of the computation as needed. Learn more in the tutorial.

Apache Kafka®, is an open-source distributed streaming platform.

AppScope, a new approach in black-box instrumentation, delivers ubiquitous, unified Telemetry from any Linux executable. It does this by simply prepending scope on the command. Any customer who uses Application Performance Management will tell you how much they love the solution but wish they could expand it to more applications. Most customers have only 10% of their apps set up for APM and supplement what they can with basic metrics. What about the remaining 80%? Enter AppScope. No language-specific instrumentation. No application developers required. AppScope works with all applications, from the CLI to production. It is language-independent and completely usable. AppScope data can be sent to any existing monitoring tool or time series database. AppScope allows Ops teams and SREs to query running applications in order to determine how they behave in any deployment context. This includes on-prem, cloud, containers and cloud.

Apache Flink is a distributed processing engine and framework for stateful computations using unbounded and bounded data streams. Flink can be used in all cluster environments and perform computations at any scale and in-memory speed. A stream of events can be used to produce any type of data. All data, including credit card transactions, machine logs, sensor measurements, and user interactions on a website, mobile app, are generated as streams. Apache Flink excels in processing both unbounded and bound data sets. Flink's runtime can run any type of application on unbounded stream streams thanks to its precise control of state and time. Bounded streams are internal processed by algorithms and data structure that are specifically designed to process fixed-sized data sets. This results in excellent performance. Flink can be used with all of the resource managers previously mentioned.

You can manage your data from the edge to the cloud with a simple, no-code approach to creating sophisticated streaming applications.

StreamSets DataOps Platform. An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. 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. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Samza lets you build stateful applications that can process data in real time from multiple sources, including Apache Kafka. It has been battle-tested at scale and supports flexible deployment options, including running on YARN or as a standalone program. Samza offers high throughput and low latency to instantly analyze your data. With features like host-affinity and incremental checkpoints, Samza can scale to many terabytes in state. Samza is easy-to-use with flexible deployment options YARN, Kubernetes, or standalone. The ability to run the same code to process streaming and batch data. Integrates with multiple sources, including Kafka and HDFS, AWS Kinesis Azure Eventhubs, Azure Eventhubs K-V stores, ElasticSearch, AWS Kinesis, Kafka and ElasticSearch.

Apache Doris is an advanced data warehouse for real time analytics. It delivers lightning fast analytics on real-time, large-scale data. Ingestion of micro-batch data and streaming data within a second. Storage engine with upserts, appends and pre-aggregations in real-time. Optimize for high-concurrency, high-throughput queries using columnar storage engine, cost-based query optimizer, and vectorized execution engine. Federated querying for data lakes like Hive, Iceberg, and Hudi and databases like MySQL and PostgreSQL. Compound data types, such as Arrays, Maps and JSON. Variant data types to support auto datatype inference for JSON data. NGram bloomfilter for text search. Distributed design for linear scaling. Workload isolation, tiered storage and efficient resource management. Supports shared-nothing as well as the separation of storage from compute.

Unified stream and batch data processing that is serverless, fast, cost-effective, and low-cost. Fully managed data processing service. Automated provisioning of and management of processing resource. Horizontal autoscaling worker resources to maximize resource use Apache Beam SDK is an open-source platform for community-driven innovation. Reliable, consistent processing that works exactly once. Streaming data analytics at lightning speed Dataflow allows for faster, simpler streaming data pipeline development and lower data latency. Dataflow's serverless approach eliminates the operational overhead associated with data engineering workloads. Dataflow allows teams to concentrate on programming and not managing server clusters. Dataflow's serverless approach eliminates operational overhead from data engineering workloads, allowing teams to concentrate on programming and not managing server clusters. Dataflow automates provisioning, management, and utilization of processing resources to minimize latency.

Baidu Stream Computing provides real-time data processing with low delay, high throughput, and high accuracy. It is compatible with Spark SQL and can process complex business logic through SQL statements. It also provides users with a full life cycle management of streaming-oriented computing jobs. As the upstream and downstream of stream computing, integrate deeply with multiple storage solutions of Baidu AI Cloud, including Baidu Kafka and RDS. Provide a comprehensive monitoring indicator for the job. The user can view monitoring indicators and set alarm rules to protect the task.

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. Memgraph's vibrant open-source community brings together over 150,000 developers in more than 100 countries to exchange ideas and optimize the next generation of in-memory data-driven applications across GenAI/ LLMs and real-time analytics performed with streaming data.

Spark Streaming uses Apache Spark's language-integrated API for stream processing. It allows you to write streaming jobs in the same way as you write batch jobs. It supports Java, Scala, and Python. Spark Streaming recovers lost work as well as operator state (e.g. Without any additional code, Spark Streaming recovers both lost work and operator state (e.g. sliding windows) right out of the box. Spark Streaming allows you to reuse the same code for batch processing and join streams against historical data. You can also run ad-hoc queries about stream state by running on Spark. Spark Streaming allows you to create interactive applications that go beyond analytics. Apache Spark includes Spark Streaming. It is updated with every Spark release. Spark Streaming can be run on Spark's standalone mode or other supported cluster resource mangers. It also has a local run mode that can be used for development. Spark Streaming uses ZooKeeper for high availability in production.

Flume is a reliable, distributed service that efficiently collects, aggregates, and moves large amounts of log data. Flume's architecture is based on streaming data flows and is simple and flexible. It is robust and fault-tolerant, with many failovers and recovery options. It is based on a simple extensible data structure that allows for online analytical applications. Flume 1.8.0 has been released by the Apache Flume team. Flume is a distributed, reliable and available service that efficiently collects, aggregates, and moves large amounts of streaming event information.

A comprehensive, component-based platform for automating data reconciliation in modern data lake and cloud data migration projects using Apache Spark. DataOps Dataflow is a modern web browser-based solution for automatically auditing ETL, Data Warehouse and Data Migration projects. Use Dataflow to bring data from one of several different data sources, compare data, and load the differences into S3 or a database. With quick and easy setup, create and run data streams in minutes. Best in 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.

Nussknacker allows domain experts to use a visual tool that is low-code to help them create and execute real-time decisioning algorithm instead of writing code. It is used to perform real-time actions on data: real-time marketing and fraud detection, Internet of Things customer 360, Machine Learning inferring, and Internet of Things customer 360. A visual design tool for decision algorithm is an essential part of Nussknacker. It allows non-technical users, such as analysts or business people, to define decision logic in a clear, concise, and easy-to-follow manner. With a click, scenarios can be deployed for execution once they have been created. They can be modified and redeployed whenever there is a need. Nussknacker supports streaming and request-response processing modes. It uses Kafka as its primary interface in streaming mode. It supports both stateful processing and stateless processing.

IBM® Event Streams, an event-streaming platform built on Apache Kafka open-source software, is a smart app that reacts to events as they occur. Event Streams is based upon years of IBM operational experience running Apache Kafka stream events for enterprises. Event Streams is ideal for mission-critical workloads. You can extend the reach and reach of your enterprise assets by connecting to a variety of core systems and using a scalable RESTAPI. Disaster recovery is made easier by geo-replication and rich security. Use the CLI to take advantage of IBM productivity tools. Replicate data between Event Streams deployments during a disaster-recovery scenario.

Responsive apps keep developers motivated and users engaged. With the DataStax Astra streaming service platform, you can meet these ever-increasing demands. DataStax Astra Streaming, powered by Apache Pulsar, is a cloud-native messaging platform and event streaming platform. Astra Streaming lets you build streaming applications on top a multi-cloud, elastically scalable and event streaming platform. Apache Pulsar is the next-generation event streaming platform that powers Astra Streaming. It provides a unified solution to streaming, queuing and stream processing. Astra Streaming complements Astra DB. Astra Streaming allows existing Astra DB users to easily create real-time data pipelines from and to their Astra DB instances. Astra Streaming allows you to avoid vendor lock-in by deploying on any major public cloud (AWS, GCP or Azure) compatible with open source Apache Pulsar.

Streaming service is a streaming service that allows developers and data scientists to stream real-time events. It is serverless and Apache Kafka compatible. Streaming can be integrated with Oracle Cloud Infrastructure, Database, GoldenGate, Integration Cloud, and Oracle Cloud Infrastructure (OCI). The service provides integrations for hundreds third-party products, including databases, big data, DevOps, and SaaS applications. Data engineers can easily create and manage big data pipelines. Oracle manages all infrastructure and platform management, including provisioning, scaling and security patching. Streaming can provide state management to thousands of consumers with the help of consumer groups. This allows developers to easily create applications on a large scale.

VeloDB, powered by Apache Doris is a modern database for real-time analytics at scale. In seconds, micro-batch data can be ingested using a push-based system. Storage engine with upserts, appends and pre-aggregations in real-time. Unmatched performance in real-time data service and interactive ad hoc queries. Not only structured data, but also semi-structured. Not only real-time analytics, but also batch processing. Not only run queries against internal data, but also work as an federated query engine to access external databases and data lakes. Distributed design to support linear scalability. Resource usage can be adjusted flexibly to meet workload requirements, whether on-premise or cloud deployment, separation or integration. Apache Doris is fully compatible and built on this open source software. Support MySQL functions, protocol, and SQL to allow easy integration with other tools.

Apache Kafka®, with Confluent, has an infinite retention. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming allows you to innovate and win by being both highly-scalable and real-time. Ever wonder how your rideshare app analyses massive amounts of data from multiple sources in order to calculate real-time ETA. Wondering how your credit card company analyzes credit card transactions from all over the world and sends fraud notifications in real time? Event streaming is the answer. Microservices are the future. A persistent bridge to the cloud can enable your hybrid strategy. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. There are many other options.

DeltaStream is an integrated serverless streaming processing platform that integrates seamlessly with streaming storage services. Imagine it as a compute layer on top your streaming storage. It offers streaming databases and streaming analytics along with other features to provide an integrated platform for managing, processing, securing and sharing streaming data. DeltaStream has a SQL-based interface that allows you to easily create stream processing apps such as streaming pipelines. It uses Apache Flink, a pluggable stream processing engine. DeltaStream is much more than a query-processing layer on top Kafka or Kinesis. It brings relational databases concepts to the world of data streaming, including namespacing, role-based access control, and enables you to securely access and process your streaming data, regardless of where it is stored.

Simplifies data transfer between components in microservices architectures. When used as a microservice transport, it simplifies integration and increases reliability. It also improves scaling. Read and write data near real-time. Set the data throughput to your needs. You can configure the resources to process data streams in granular detail, from 100 KB/s up to 100 MB/s. Yandex Data Transfer allows you to send a single data stream to multiple destinations with different retention policies. Data is automatically replicated over multiple geographically dispersed availability zones. Once created, data streams can be managed centrally via the management console or API. Yandex Data Streams is able to collect data continuously from sources such as website browsing histories, system and application logs, or social media feeds. Yandex Data Streams can continuously collect data from sources like website browsing histories, logs of application, etc.

GS RichCopy 360 Standard data migration software is enterprise-grade. It copies your data (files, folders) to another place. Multi-threading technology allows files to be copied simultaneously. It offers the following premium features: - Copy files to Office 365 OneDrive or SharePoint - Copy open files. - Copy NTFS permissions. - Support Long Path Name - Run as a service and according to a scheduler (you don't need to log in). - Copy folder and file attributes as well as time stamps. Send an email to confirm. Support by phone and email - Simple to use

In the field of IoT stream processing and analytics, SQLstream ranks #1 according to ABI Research. Used by Verizon, Walmart, Cisco, and Amazon, our technology powers applications on premises, in the cloud, and at the edge. SQLstream enables time-critical alerts, live dashboards, and real-time action with sub-millisecond latency. Smart cities can reroute ambulances and fire trucks or optimize traffic light timing based on real-time conditions. Security systems can detect hackers and fraudsters, shutting them down right away. AI / ML models, trained with streaming sensor data, can predict equipment failures. Thanks to SQLstream's lightning performance -- up to 13 million rows / second / CPU core -- companies have drastically reduced their footprint and cost. Our efficient, in-memory processing allows operations at the edge that would otherwise be impossible. Acquire, prepare, analyze, and act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code, GUI dev environment. Edit scripts instantly and view instantaneous results without compiling. Deploy with native Kubernetes support. Easy installation includes Docker, AWS, Azure, Linux, VMWare, and more

You can deliver customer experiences like never before with breakthrough data streaming capabilities Both the ecosystem and Kafka API are compatible. Redpanda BulletPredictable low latency with zero data loss. Redpanda BulletUp to 10x faster than Kafka Redpanda BulletEnterprise-grade support and hotfixes. Redpanda BulletAutomated backups for S3/GCS. Redpanda Bullet100% freedom of routine Kafka operations. Redpanda BulletSupports for AWS/GCP. Redpanda was built from the ground up to be easy to install and get running quickly. Redpanda's power will be evident once you have tried it in production. You can use the more advanced Redpanda functions. We manage all aspects of provisioning, monitoring, as well as upgrades. We do not have access to your cloud credentials. Sensitive data never leaves your environment. You can have it provisioned, operated, maintained, and updated for you. Configurable instance types. As your needs change, you can expand the cluster.

Pipes is a new way of creating queries and shaping data. It's inspired by Python Notebooks. This is a simplified way to increase performance without sacrificing complexity. Splitting your query into multiple nodes makes it easier to develop and maintain. You can activate your production-ready API endpoints in one click. Transforms happen on-the-fly, so you always have the most current data. You can share secure access to your data with one click, and get consistent results. Tinybird scales linearly, so don't worry if you have high traffic. Imagine if you could transform any Data Stream or CSV file into a secure real-time analytics API endpoint in a matter minutes. We believe in high-frequency decision making for all industries, including retail, manufacturing and telecommunications.

You can quickly collect, process, analyze, and analyze video and data streams. Amazon Kinesis makes it easy for you to quickly and easily collect, process, analyze, and interpret streaming data. Amazon Kinesis provides key capabilities to process streaming data at any scale cost-effectively, as well as the flexibility to select the tools that best fit your application's requirements. Amazon Kinesis allows you to ingest real-time data, including video, audio, website clickstreams, application logs, and IoT data for machine learning, analytics, or other purposes. Amazon Kinesis allows you to instantly process and analyze data, rather than waiting for all the data to be collected before processing can begin. Amazon Kinesis allows you to ingest buffer and process streaming data instantly, so you can get insights in seconds or minutes, instead of waiting for hours or days.

In a developer-friendly visual editor, you can design, debug, run, and troubleshoot data jobflows and data transformations. You can orchestrate data tasks that require a specific sequence and organize multiple systems using the transparency of visual workflows. Easy deployment of data workloads into an enterprise runtime environment. Cloud or on-premise. Data can be made available to applications, people, and storage through a single platform. You can manage all your data workloads and related processes from one platform. No task is too difficult. CloverDX was built on years of experience in large enterprise projects. Open architecture that is user-friendly and flexible allows you to package and hide complexity for developers. You can manage the entire lifecycle for a data pipeline, from design, deployment, evolution, and testing. Our in-house customer success teams will help you get things done quickly.

The RecordPoint Data Trust platform helps highly regulated organizations manage data throughout its lifecycle, regardless of system. We work with organizations in highly regulated industries to ensure their data is right where it should be - safeguarded for privacy, security, and governance.

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 a FREE download from OS FORGE Did you... You need to upgrade servers and migrate apps, but now you must migrate the data & light BPT or BPT? To populate lookup data, you will need to migrate data from the Qual to Prod Environment. You need to move from Prod to Quali to replicate problems or get a good QA environment to test. Do you need to back up data to be able later to restore a demo environment? Do you need to import data from other systems into OutSystems? Do you need to validate performance? What is Infosistema DMM? https://www.youtube.com/watch?v=strh2TLliNc Reduce costs, reduce risks, and increase time-to market DMM is the fastest way to solve a problem!

Get a free report that includes a detailed analysis and analysis of your source code. A migration engineer can help you plan how to migrate your project. A quick phone call can give valuable insight into which workloads can be made cloud ready quickly and which may need more effort. VB6 has been out-of-support for more than a decade. Visual Basic Upgrade Companion efficiently and quickly migrates VB6 code from VB6 to C#, VB.NET,.NET Core or Framework using Windows Forms. It is faster than a rewrite and more productive than any other solutions. VBUC moves forms and business logic to.NET Framework Core. This preserves the integrity of proven and debugged processes and logic. Complex web apps are possible. WebMAP allows you to move your.NET and PowerBuilder apps to the native web using Angular or ASP.NET Core, hiding the clutter.

Businesses are shifting their collaboration and communication systems to the cloud. To protect against vendor lock-in, downtime, and other issues, they need a separate backup or archive of their data on a different cloud. Data loss and theft are more common in data operations that require a lot of human effort. New tools must support large data types and have strong data integrity checks to ensure that large data volumes can be quickly and error-free migrated. Old software needs physical hardware to be provisioned. It is also not designed to handle the new Saas-generated data. These tools require a high level of human effort to transform data. As cloud communication services become more popular, large amounts of data are generated. These data require systems that can be automated and scale easily. You will need to use automation and hands-free to ensure the security of the data being processed.

Talend Open Studio makes it easy to build basic data pipelines. You can perform simple ETL and data integration tasks. You can also get graphical profiles of your data and manage files from an open-source environment you have locally. Talend Cloud is the right tool for you if your project is ready to go. Open Studio's intuitive interface is available to you, as well as the tools for collaboration and monitoring that are required for ongoing projects. You can add data quality, big-data integration, and processing resources easily. Also, you can take advantage of the latest analytics technologies and elastic capacity from AWS and Azure whenever you need it. Join the Talend Community to get started on your data integration journey. The Talend Community is for everyone, beginner or expert. It's the place to share best practices and find new tricks.

SmartParse simplifies data migrations from any flat-file to any API, with minimal setup. It offers a quick and low-code solution to integrate systems. It can handle files with a few lines to millions.

GS RichCopy 360, a data migration software for enterprises, is available. It copies your data (files, folders) to another place. Multi-threading technology allows files to be copied simultaneously. It offers the following premium features: Copy to Office 365 OneDrive or SharePoint Copy open files Copy NTFS permissions - Support Long Path Name - Run as a service and according to a scheduler (you don't need to log in). - Copy folder and file attributes as well as time stamps. - When it is complete, send an email. Support by phone and email - Simple to use - Copy data using one TCP port across the internet, and have it encrypted as it is being transferred. - Bite level replication (copy only deltas in the file, not the entire file). Superior and robust performance. - Supports Windows 7 or later (Windows 8, Windows8.1, Windows 10). - Supports Windows Server 2008R2 or Later (Windows Server 2012 R2, 2016, and 2019).

Supported data migrations are available on-premises or cloud-based for nearly 20 data sources. The distributed computing framework allows for high-performance data migrations and optimized data writing for specific data sources. The wizard-based development interface makes it easy to quickly develop migration tasks and frees you from the burden of complex programming. You only pay for the services you use. You don't need to purchase hardware or software. Big data cloud services can be used to replace or back-up on-premises big databases and allow for full data migration. A wide range of data sources are supported, including big data, files, NoSQL and relational databases. Wizard-based task management allows for easy use. Data mobility is achieved by data migration between services on HUAWEI CLOUD.

Qlik Replicate (formerly Attunity Replicate), is a high-performance replication tool that optimizes data ingestion from a wide range of data sources and platforms. It also seamlessly integrates with all major big-data analytics platforms. Replicate supports both bulk replication and real-time incremental replica using CDC (change information capture). Our unique zero footprint architecture reduces overhead on mission-critical systems and allows for zero downtime data migrations and database upgrade.

Our state-of the-art data migration tool is specifically designed to convert and migrate data from legacy applications to advanced systems and frameworks. It also includes advanced data validation mechanisms and real-time reporting.

iCEDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iCEDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iCEDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iCEDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.

MSSQL to PostgreSQL is a tool that allows you to migrate databases between SQL Server and Azure SQL, to PostgreSQL cloud or on-premises DBMS. The program is fast due to low-level algorithms for reading and writing data. It can read and write more than 10MB per second. Command line support is available to automate migration.

Ispirer SQLWays is a simple-to-use tool for cross-database migration. It allows you to migrate your entire database schema including SQL objects, tables, and data, from the source to the target databases. All of these capabilities can be combined into one solution: smart conversion, teamwork and technical support, tool customization based on your project requirements, etc. Customization option. The migration process can be tailored to meet specific business requirements using SQLWays Toolkit. It accelerates database modernization. High level of automation. Smart migration core offers a high degree of automation to the migration process. This ensures a consistent, reliable migration. Code security. We place great importance on privacy. We developed a tool that does neither save nor send the code structures. Our tool will ensure that your data remains safe as it can operate without an internet connection.

MigrationPro is an online Shopping Cart Migration Service designed to help e-commerce companies, web agencies and various online retailers migrate their store data efficiently from one platform into another. The service is compatible with a wide range of ecommerce platforms including Shopify BigCommerce WooCommerce Magento PrestaShop. The tool automates the complex data migration process, ensuring the precise transfer of store components such as product details, customer details, or order histories. It places a strong emphasis on maintaining data security and operational continuity during the transition. This minimizes any potential disruptions in business activities, while guaranteeing the integrity migrated data. MigrationPro has a flexible pricing structure that is based on the data entities a user chooses to transfer. This allows for different scalability requirements.

Ispirer nGLFly Wizard manages cross-platform migration. The tool automatically migrates the source code between two languages. The tool can also change the architecture of an application, such as from desktop to web based. The software optimizes migration to reduce time and ensure high-quality migration. We modernize legacy applications. COBOL, Progress 4GL Informix 4GL Delphi, PowerBuilder, and Informix 4GL to modern technologies including WEB architecture provided by the.NET ecosystem and Java ecosystem.

Stelo is an enterprise-class tool which dynamically delivers data anywhere to anywhere. It can be used for analysis, prediction, and reporting, as well as for managing business operations and supply chains. You can easily move data between your core relational databases or delta lakes across firewalls, to other people, or to the Cloud. Stelo Data Replicator offers reliable, fast, and affordable replication for any relational or non-relational database via ODBC, Kafka, Delta Lakes, and flat file formats. Stelo uses native data loading functions and multithreaded processing for fast, reliable performance when replicating multiple tables simultaneously. Easy installation using GUI interfaces, configuration wizards and advanced tools makes product setup and operation simple, without the need for programming. Stelo runs in the background and requires no engineering support.

IBM Cloud®, Mass Data Migration uses 120 TB storage capacity to speed up data migration to the cloud. It also overcomes common transfer challenges such as long transfer times, high costs, and security concerns. All this in one service. You can migrate up 120 TB (at RAID-6) of data using one IBM Cloud Mass Data Migration device in days. This is in contrast to traditional data-transfer methods that can take weeks or months. You can request one or more devices depending on how large your data needs are. Large data sets can be costly and time-consuming to move. For only 50 USD per day, you can use an IBM Cloud Mass Data Migration device at home. IBM will send you a pre-configured device that you can use to connect, ingest data, and then ship it back to IBM to offload into IBM Cloud Object Storage. After the device is offloaded, you can immediately access your data in the cloud while IBM secure wipes it.