Best Data Pipeline Software for Apache Kafka

Hevo Data is a no-code, bi-directional data pipeline platform specially built for modern ETL, ELT, and Reverse ETL Needs. It helps data teams streamline and automate org-wide data flows that result in a saving of ~10 hours of engineering time/week and 10x faster reporting, analytics, and decision making. The platform supports 100+ ready-to-use integrations across Databases, SaaS Applications, Cloud Storage, SDKs, and Streaming Services. Over 500 data-driven companies spread across 35+ countries trust Hevo for their data integration needs.

RudderStack is the smart customer information pipeline. You can easily build pipelines that connect your entire customer data stack. Then, make them smarter by pulling data from your data warehouse to trigger enrichment in customer tools for identity sewing and other advanced uses cases. Start building smarter customer data pipelines today.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Open source solutions that require no maintenance can save you time and money. Your engineers will enjoy working with data because it is integrated, managed and highly reliable. DoubleCloud offers a range of managed open-source services, or you can leverage the full platform's power, including data storage and visualization, orchestration, ELT and real-time visualisation. We offer leading open-source solutions like ClickHouse Kafka and Airflow with deployments on Amazon Web Services and Google Cloud. Our no-code ELT allows real-time data sync between systems. It is fast, serverless and seamlessly integrated into your existing infrastructure. Our managed open-source data visualisation allows you to visualize your data in real time by creating charts and dashboards. Our platform is designed to make engineers' lives easier.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

All your ELT data pipelines, including custom ones, will be up and running in minutes. Your team can focus on innovation and insights. Unify all your data integration pipelines with one open-source ELT platform. Airbyte can meet all the connector needs of your data team, no matter how complex or large they may be. Airbyte is a data integration platform that scales to meet your high-volume or custom needs. From large databases to the long tail API sources. Airbyte offers a long list of connectors with high quality that can adapt to API and schema changes. It is possible to unify all native and custom ELT. Our connector development kit allows you to quickly edit and create new connectors from pre-built open-source ones. Transparent and scalable pricing. Finally, transparent and predictable pricing that scales with data needs. No need to worry about volume. No need to create custom systems for your internal scripts or database replication.

You can deploy production-ready change data capture pipes for high-volume, real time data replication without writing a single line code. Supercharged Change Data Capture. Arcion's distributed Change Data Capture, CDC, allows for automatic schema conversion, flexible deployment, end-to-end replication and much more. Arcion's zero-data loss architecture ensures end-to-end consistency and built-in checkpointing. You can forget about performance and scalability concerns with a distributed, highly parallel architecture that supports 10x faster data replication. Arcion Cloud is the only fully managed CDC offering. You'll enjoy autoscaling, high availability, monitoring console and more. Reduce downtime and simplify data pipelines architecture.

Many components are required to build real-time apps or services. These components include Kafka and VPC hosting, infrastructure code, container orchestration and observability. The Quix platform handles all the moving parts. Connect your data and get started building. That's it. There are no provisioning clusters nor configuring resources. You can use Quix connectors for ingesting transaction messages from your financial processing system in a virtual private clouds or on-premise data centers. For security and efficiency, all data in transit is encrypted from the beginning and compressed using Protobuf and G-Zip. Machine learning models and rule-based algorithms can detect fraudulent patterns. You can display fraud warning messages in support dashboards or as troubleshooting tickets.

StreamNative redefines the streaming infrastructure by integrating Kafka MQ and other protocols into a unified platform that provides unparalleled flexibility and efficiency to modern data processing requirements. StreamNative is a unified platform that adapts to diverse streaming and messaging requirements in a microservices environment. StreamNative's comprehensive and intelligent approach to streaming and messaging empowers organizations to navigate with efficiency and agility the complexity and scalability in the modern data ecosystem. Apache Pulsar’s unique architecture decouples message storage from the message serving layer, resulting in a cloud-native data streaming platform. Scalable and elastic, allowing it to adapt to changing business needs and event traffic. Scale up to millions of topics using architecture that decouples computing from storage.

GlassFlow is an event-driven, serverless data pipeline platform for Python developers. It allows users to build real time data pipelines, without the need for complex infrastructure such as Kafka or Flink. GlassFlow is a platform that allows developers to define data transformations by writing Python functions. GlassFlow manages all the infrastructure, including auto-scaling and low latency. Through its Python SDK, the platform can be integrated with a variety of data sources and destinations including Google Pub/Sub and AWS Kinesis. GlassFlow offers a low-code interface that allows users to quickly create and deploy pipelines. It also has features like serverless function executions, real-time connections to APIs, alerting and reprocessing abilities, etc. The platform is designed for Python developers to make it easier to create and manage event-driven data pipes.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

Lyftrondata can help you build a governed lake, data warehouse or migrate from your old database to a modern cloud-based data warehouse. Lyftrondata makes it easy to create and manage all your data workloads from one platform. This includes automatically building your warehouse and pipeline. It's easy to share the data with ANSI SQL, BI/ML and analyze it instantly. You can increase the productivity of your data professionals while reducing your time to value. All data sets can be defined, categorized, and found in one place. These data sets can be shared with experts without coding and used to drive data-driven insights. This data sharing capability is ideal for companies who want to store their data once and share it with others. You can define a dataset, apply SQL transformations, or simply migrate your SQL data processing logic into any cloud data warehouse.

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.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

BDB is a modern data analysis and BI platform that can dig deep into your data to uncover actionable insights. It can be deployed on-premise or in the cloud. Our unique microservices-based architecture includes elements such as Data Preparation and Predictive, Pipeline, Dashboard designer, and Pipeline. This allows us to offer customized solutions and scalable analysis to different industries. BDB's NLP-based search allows users to access the data power on desktop, tablet, and mobile. BDB is equipped with many data connectors that allow it to connect to a variety of data sources, apps, third-party API's, IoT and social media. It works in real-time. It allows you to connect to RDBMS and Big data, FTP/ SFTP Server flat files, web services, and FTP/ SFTP Server. You can manage unstructured, semi-structured, and structured data. Get started on your journey to advanced analysis today.

Conduktor is the all-in one interface that allows you to interact with the Apache Kafka ecosystem. You can confidently develop and manage Apache Kafka. Conduktor DevTools is the all-in one Apache Kafka desktop client. You can manage Apache Kafka confidently and save time for your whole team. Apache Kafka can be difficult to learn and use. Conduktor is loved by developers for its best-in-class user interface. Conduktor is more than an interface for Apache Kafka. Conduktor gives you and your team control over your entire data pipeline thanks to its integration with many technologies around Apache Kafka. It gives you and your team the most comprehensive tool for Apache Kafka.

BigBI allows data specialists to create their own powerful Big Data pipelines interactively and efficiently, without coding! BigBI unleashes Apache Spark's power, enabling: Scalable processing of Big Data (upto 100X faster). Integration of traditional data (SQL and batch files) with new data Sources include semi-structured data (JSON, NoSQL DBs and Hadoop) as well as unstructured data (text, audio, video). Integration of streaming data and cloud data, AI/ML graphs & graphs