Compare Etleap vs. IBM StreamSets

Fivetran is a comprehensive data integration solution designed to centralize and streamline data movement for organizations of all sizes. With more than 700 pre-built connectors, it effortlessly transfers data from SaaS apps, databases, ERPs, and files into data warehouses and lakes, enabling real-time analytics and AI-driven insights. The platform’s scalable pipelines automatically adapt to growing data volumes and business complexity. Leading companies such as Dropbox, JetBlue, Pfizer, and National Australia Bank rely on Fivetran to reduce data ingestion time from weeks to minutes and improve operational efficiency. Fivetran offers strong security compliance with certifications including SOC 1 & 2, GDPR, HIPAA, ISO 27001, PCI DSS, and HITRUST. Users can programmatically create and manage pipelines through its REST API for seamless extensibility. The platform supports governance features like role-based access controls and integrates with transformation tools like dbt Labs. Fivetran helps organizations innovate by providing reliable, secure, and automated data pipelines tailored to their evolving needs.

AWS Glue is a fully managed data integration solution that simplifies the process of discovering, preparing, and merging data for purposes such as analytics, machine learning, and application development. By offering all the necessary tools for data integration, AWS Glue enables users to begin analyzing their data and leveraging it for insights within minutes rather than taking months. The concept of data integration encompasses various activities like identifying and extracting data from multiple sources, enhancing, cleaning, normalizing, and consolidating that data, as well as organizing and loading it into databases, data warehouses, and data lakes. Different users, each utilizing various tools, often manage these tasks. Operating within a serverless environment, AWS Glue eliminates the need for infrastructure management, automatically provisioning, configuring, and scaling the resources essential for executing data integration jobs. This efficiency allows organizations to focus more on data-driven decision-making without the overhead of manual resource management.

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

Tenzir is a specialized data pipeline engine tailored for security teams, streamlining the processes of collecting, transforming, enriching, and routing security data throughout its entire lifecycle. It allows users to efficiently aggregate information from multiple sources, convert unstructured data into structured formats, and adjust it as necessary. By optimizing data volume and lowering costs, Tenzir also supports alignment with standardized schemas such as OCSF, ASIM, and ECS. Additionally, it guarantees compliance through features like data anonymization and enhances data by incorporating context from threats, assets, and vulnerabilities. With capabilities for real-time detection, it stores data in an efficient Parquet format within object storage systems. Users are empowered to quickly search for and retrieve essential data, as well as to reactivate dormant data into operational status. The design of Tenzir emphasizes flexibility, enabling deployment as code and seamless integration into pre-existing workflows, ultimately seeking to cut SIEM expenses while providing comprehensive control over data management. This approach not only enhances the effectiveness of security operations but also fosters a more streamlined workflow for teams dealing with complex security data.

DataBahn is an advanced platform that harnesses the power of AI to manage data pipelines and enhance security, streamlining the processes of data collection, integration, and optimization from a variety of sources to various destinations. Boasting a robust array of over 400 connectors, it simplifies the onboarding process and boosts the efficiency of data flow significantly. The platform automates data collection and ingestion, allowing for smooth integration, even when dealing with disparate security tools. Moreover, it optimizes costs related to SIEM and data storage through intelligent, rule-based filtering, which directs less critical data to more affordable storage options. It also ensures real-time visibility and insights by utilizing telemetry health alerts and implementing failover handling, which guarantees the integrity and completeness of data collection. Comprehensive data governance is further supported by AI-driven tagging, automated quarantining of sensitive information, and mechanisms in place to prevent vendor lock-in. In addition, DataBahn's adaptability allows organizations to stay agile and responsive to evolving data management needs.

Cribl Stream allows you create an observability pipeline that helps you parse and restructure data in flight before you pay to analyze it. You can get the right data in the format you need, at the right place and in the format you want. Translate and format data into any tooling scheme you need to route data to the right tool for the job or all of the job tools. Different departments can choose different analytics environments without the need to deploy new forwarders or agents. Log and metric data can go unused up to 50%. This includes duplicate data, null fields, and fields with zero analytical value. Cribl Stream allows you to trim waste data streams and only analyze what you need. Cribl Stream is the best way for multiple data formats to be integrated into trusted tools that you use for IT and Security. Cribl Stream universal receiver can be used to collect data from any machine source - and to schedule batch collection from REST APIs (Kinesis Firehose), Raw HTTP and Microsoft Office 365 APIs.

SAP Integration Suite is a robust integration platform as a service (iPaaS) that facilitates the seamless connection of both on-premise and cloud-based applications and processes through a variety of tools and prebuilt content curated by SAP. By utilizing these tools and prebuilt resources, organizations can effectively tackle a wide array of integration challenges, which encompass integration flows, connectivity to third-party solutions, and managing APIs. This platform enables enterprises to connect and personalize experiences, fostering a culture of innovation that begins with integration. It empowers users beyond just central IT, allowing for greater flexibility and creativity in integration processes. The iPaaS solution provides a cloud service designed for various integration scenarios, including application, data, process, and service-oriented architecture (SOA) integrations. As a multitenant platform, it supports diverse integration types such as cloud-to-cloud, cloud-to-on-premise, on-premise-to-on-premise, and B2B integration. Moreover, it is optimized for real-time integration, ensuring that it can scale to accommodate the high-volume demands of mobile applications and electronic data interchange environments, thus enhancing operational efficiency across the board. This versatility makes SAP Integration Suite an essential tool for organizations looking to streamline and enhance their integration strategies.

Boomi's iPaaS platform empowers businesses to integrate, automate, and manage their data and workflows across multiple applications and systems. By leveraging AI agents, Boomi automates complex processes, improving speed and reducing errors. With a user-friendly interface and a library of pre-built connectors, the platform simplifies the integration of applications such as Salesforce, SAP, and AWS. Boomi helps organizations unlock their full potential by enabling rapid digital transformation, secure data management, and optimized business operations. Boomi Agentstudio is the solution for managing AI agents at scale, offering businesses a centralized platform to design, monitor, and deploy agents effectively. It includes powerful tools such as Agent Garden for lifecycle management, Agent Control Tower for visibility and governance, and AI-powered workflows that integrate seamlessly with other business systems. By providing easy-to-use tools for AI agent orchestration, Boomi allows organizations to achieve efficient, compliant automation while reducing operational complexities, all within a secure environment.