Best Data Integration Tools in 2026

Fivetran is a managed data movement service that replicates data from SaaS applications, databases, files and event streams into cloud warehouses and lakes, using pre-built connectors that adapt automatically to schema changes. Its Standard plan lists more than 700 fully managed connectors, more than 200 activation destinations for reverse ETL, a feature that Fivetran's documentation connects to its Census product heritage, and integration with dbt Core for transformations. On 1 June 2026 Fivetran and dbt Labs completed a merger; the combined company, Fivetran + dbt Labs, is led by George Fraser as chief executive and Tristan Handy as president, and states that it serves more than 100,000 data teams. Pricing is usage-based on monthly active rows (MAR), the number of distinct rows inserted, updated or deleted in a month, with a free plan of up to 500,000 MAR, a US$5 base charge for connections between 1 and 1 million MAR, and discounts of up to 22% on annual contracts. Fivetran's strength is low-maintenance ingestion at scale. Its MAR model is difficult to forecast for high-churn sources, and it is less suited to complex in-flight transformation or application-to-application integration.

Informatica is one of the longest-established enterprise data integration vendors, and its Intelligent Data Management Cloud (IDMC) combines data integration, application integration, data quality, catalog, governance, privacy and master data management on one platform. Salesforce completed its acquisition of Informatica on 18 November 2025, saying the deal would bring Informatica's catalog, integration, governance, quality, metadata and MDM services to the Salesforce platform. IDMC is sold on consumption-based pricing, in which customers buy units that can be spent across multiple services and scale volumes over time, and Informatica states that more than 5,000 enterprises use its products. The platform is strongest in large, regulated organisations with many on-premises and cloud systems, where its breadth, mature data quality and MDM, and long connector history matter. The trade-offs are cost and complexity, the need for specialist skills, and uncertainty for non-Salesforce customers about product direction under the new owner.

Qlik Talend Cloud is Qlik's data integration platform, formed after Qlik acquired Talend, an integration, data quality and governance vendor; Qlik described the combination as joining its data integration with Talend's transformation, quality and governance capabilities. The platform covers data movement from SaaS applications and databases, real-time change data capture (CDC) replication, ELT and ETL transformations, data warehouse and lakehouse automation, column-level lineage, data quality and data products. Plans run from Starter, for moving data from SaaS applications and databases in a few clicks, to Standard, which adds real-time CDC at scale, and higher Premium and Enterprise tiers with transformation, Spark processing and governance; prices are not published and are obtained from sales. Qlik's change data capture technology is widely used for replicating operational databases into analytics platforms with low latency. The combined product range is broad, which can make edition choice and licensing complicated,

Airbyte is a data movement platform whose core, Airbyte Core, is open source and free to self-host, with a Connector Builder for creating custom sources. Its cloud plans add hosting, upgrades and support. Standard starts at US$20 per month with syncs as often as hourly; Plus, positioned as best value above 10 GB, starts at US$189 per month for 40 credits and adds SSO and 15-minute syncs; Pro offers a flat annual capacity price with syncs every five minutes; and Enterprise Flex runs data planes in the customer's VPC, on premises or across regions so that data does not leave the customer's environment. A 14-day trial includes 400 credits, about 100 GB of syncs. Airbyte is popular with engineering teams that want to customise connectors or avoid row-based pricing. Self-hosting requires operating the platform's infrastructure, and connector quality varies, with community-maintained connectors generally less mature than those a fully managed vendor certifies.

Matillion is a data integration vendor focused on loading and transforming data inside cloud data platforms. Its Data Productivity Cloud provides connectors, a low-code pipeline canvas with SQL and Python, orchestration and a built-in Git repository, while its older Matillion ETL product remains available. The company's current emphasis is Maia, an AI agent that builds, manages and orchestrates pipelines, which can be trialled in the Data Productivity Cloud on a time-bound, fair-use basis. Pricing is consumption-based on credits, with plans differing in features and users: a Developer plan for a single user with unlimited projects and pre-built connectors, a Teams plan with five developer users, an audit log and an SLA, and a Scale plan for larger organisations. Matillion is used by analytics engineering teams that want visual pipeline design combined with push-down transformation in the warehouse. Credit prices are not shown on the pricing page, and the shift toward agent-driven pipeline building is recent.

Boomi is an integration platform as a service (iPaaS) vendor whose Enterprise Platform covers application and data integration, API management, master data (Data Hub), data orchestration and CDC replication of databases into cloud warehouses. Its connector marketplace includes common enterprise applications such as SAP, Salesforce, ServiceNow, Oracle NetSuite, Workday and Snowflake. Boomi is best known for low-code process integration between business applications, for example synchronising orders, customers and employees across ERP, CRM and HR systems, rather than bulk analytics ingestion. It offers subscription plans by capability, such as Integration and Professional editions with advanced process orchestration and workflow, and a pay-as-you-go option with usage-based pricing; a 30-day trial covers the full platform. The breadth of the platform suits mid-sized and large organisations integrating many SaaS applications. Prices are not listed on the page, and data teams focused purely on warehouse loading may find dedicated ELT tools simpler.

MuleSoft's Anypoint Platform is an integration and API management platform built around API-led connectivity: systems are exposed through reusable APIs that other applications and, increasingly, AI agents consume. The platform covers application integration, API governance, automation, document processing and agent management, with a gateway that enforces security, rate limits and token budgets across API and AI calls. MuleSoft introduced new pricing in which a single type of credit, Mule Credits, is spent on integrations, APIs, automation and agents, with packages starting at US$2,000 per month and rates up to 90% lower as usage scales; a free start option is offered. MuleSoft is aimed at large enterprises that need governed APIs across many systems. It is less suited to analytics teams that only need to replicate data into a warehouse, and it requires developers skilled in its tooling.

AWS Glue is Amazon Web Services' serverless data integration service. It runs extract, transform and load jobs on Apache Spark, Spark Streaming, Ray (in preview) or Python Shell, uses crawlers to discover data and populate the AWS Glue Data Catalog, and offers Glue Studio job notebooks for interactive development. Customers pay an hourly rate, billed by the second, for crawlers and ETL jobs, measured in data processing units (DPU-hours) with a one-minute minimum on recent Glue versions, and a monthly fee for storing and accessing Data Catalog metadata, with the first million objects stored free. Glue is the default ETL choice for organisations building data lakes on Amazon S3 and querying them with AWS analytics services, because it requires no infrastructure and integrates with AWS identity and governance. Its limitations are a narrower library of SaaS connectors than specialist ELT vendors, Spark-oriented development that requires engineering skills, and costs that depend on job tuning.

Azure Data Factory is Microsoft's cloud data integration and orchestration service. Pipelines are composed of activities, such as copy, data flow and control-flow steps, executed on integration runtimes that can be serverless in Azure or self-hosted to reach on-premises sources. Mapping data flows provide visual, Spark-based transformation. Pricing is consumption-based: customers pay for pipeline orchestration per activity run, for activity execution by integration runtime hours (with data movement measured in data integration unit hours), for data flow execution and debugging, and for Data Factory operations such as creating and monitoring pipelines. Microsoft also offers a Data Factory experience inside Microsoft Fabric. Data Factory is the default integration service for Azure-centred organisations, and its self-hosted integration runtime is the usual route for reaching on-premises databases from Azure. Its pricing has many meters, and its SaaS connector coverage and developer experience are less specialised than those of dedicated ELT vendors.

Cloud Data Fusion is Google Cloud's fully managed, visual data integration service for building ETL and ELT pipelines and replication jobs, including replication into BigQuery. Pipelines execute on clusters of Google's Managed Service for Apache Spark that Data Fusion creates, and the Enterprise edition adds role-based access control for production use. Pricing has two parts: an hourly instance charge by edition, billed by the minute, and the cost of the Spark clusters that run pipelines. The Developer edition costs US$0.35 per hour, the Basic edition is free for the first 120 hours per month per account and US$1.80 per hour thereafter, and the Enterprise edition costs US$4.20 per hour. Data Fusion suits Google Cloud customers who want visual, code-free pipeline development feeding BigQuery. Its instance-hour pricing makes always-on Enterprise instances costly for small workloads, and many teams on Google Cloud use BigQuery's own transfer services or third-party ELT tools for SaaS sources instead.

SnapLogic is an integration platform as a service that covers data integration with visual ETL and ELT, application integration and API management, and markets itself as an agentic integration and applied AI platform. Pipelines are assembled from Snaps, pre-built connectors to applications, databases and services, in a browser-based designer, and the company also offers SLIM, a tool aimed at modernising legacy integration code. SnapLogic targets enterprise IT and business teams that want one low-code platform for both data pipelines and application workflows, with use cases such as employee onboarding, quote-to-cash and invoice processing, as well as OEM and embedded integration. It cites a Forrester Total Economic Impact study commissioned for the company, which reported US$3.3 million in quantified benefits over three years for a composite organisation. Prices are not published. Buyers comparing it with Boomi or MuleSoft should evaluate connector coverage for their own systems and the depth of data transformation versus dedicated ELT tools.

Hevo Data is a no-code data pipeline platform that ingests data from databases and SaaS applications into cloud warehouses. It lists more than 190 high-throughput connectors, database replication with CDC, SaaS replication, transformations using dbt, SQL and Hevo Transformer jobs, observability and alerts, and governance controls. Hevo's pricing is based on events, the records it processes, rather than monthly active rows. The Starter plan costs US$299 per month for 5 million events (US$265 per month billed annually, a 12% saving) and includes one-hour scheduling, up to 10 users and dbt integration, and the Professional plan starts at US$849 per month for 20 million events; higher tiers are available. Hevo is aimed at mid-market companies that want Fivetran-style managed ingestion at predictable cost. Its connector catalogue is smaller than Fivetran's or Airbyte's, and the shortest sync intervals and advanced features are reserved for higher plans.

Estuary is a data movement platform built around real-time change data capture and streaming, which also supports batch integration. Its product offers log-based replication from databases, real-time delivery to warehouses, lakes and other destinations, scheduled batch loads, in-flight transformation and automatic schema evolution, with deployment in Estuary's public cloud, privately or in the customer's own cloud. Pricing is published: a free Developer plan covers up to 10 GB per month and two connectors, and the Cloud pay-as-you-go plan charges US$0.50 per GB plus US$100 per month per connector instance, falling to US$50 after the sixth, with annual plans carrying volume discounts. Estuary suits teams that need sub-minute data freshness for operational analytics or AI applications without running Kafka and Debezium themselves. As a younger vendor, it has a smaller connector catalogue and installed base than established ELT providers, and per-connector charges add up for estates with many sources.