Best ETL Tools - Page 14

Data Explorer

Data Integration and Universal Database Development IDE. Data Explorer allows you to create complex data integration and ETL scenarios using drag&drop visual designer and scripting languages such as JavaScript. The universal database development IDE is integrated right into Data Explorer. It works equally well with SQL and NoSQL data sources, as well as popular file formats and APIs.

DataFactory

Datagator

Datagator protects data at rest, in a database. This is an Extract, Transform, Load (ETL) solution that protects large amounts of data (up to petabytes) being moved from a source to a target

DataGrine Migration Platform

DataGrine Migration Platform moves helpdesk data between customer support platforms: companies, contacts, tickets and conversations with their replies, notes and attachments, and knowledge base articles. Every migration starts with a written field mapping and a sample run of your own records in the destination. The full run happens while your team keeps working, a delta run at cut-over carries only what changed, and every record is logged so a run can be audited or rolled back. Runs are paced to each platform's API allowance. The platform runs Freshdesk and Intercom migrations in both directions, with Zendesk in preview; other routes are delivered by the DataGrine team as a managed migration.

Data Migration Tools

Built by the founding team at ClonePartner, Data-Migration-Tools.com provides an enterprise-grade suite of utilities designed to simplify complex system transitions. These tools are completely secure and work locally in your browser, meaning your data never leaves your system. Our Complete List of Nine Purpose Built Tools: CSV to SQL: Converts CSV dumps directly into optimized SQL INSERT statements. Vendor Evaluator: Provides a scorecard to compare external migration vendors and tools. COI and ROI Calculator: Computes the Cost of Inaction and highlights your potential migration savings. CSV to and from JSON: Offers bidirectional conversion for flat and nested data structures. XML to and from JSON: Parses legacy XML into modern JSON formats instantly. Data Profiler: Analyzes data quality by identifying null values and formatting errors. Helpdesk Evaluator: Finds the best support platform and plan for your specific business scale. Timeline Planner: Estimates your exact data migration duration based on overall volume. Helpdesk Migration Planner: Calculates precise timelines while identifying all migratable items.

Data Nexus by Dart Health

Data Nexus by Dart Health is a managed EDI and data integration service for employer health and benefits data. It ingests eligibility, claims and leave feeds from employers, TPAs, carriers and HRIS platforms, validates each record, and delivers the data through one documented REST API. Unlike self-serve file importers, Data Nexus includes a benefits-specific member data model and a Dart team that runs feed setup and exception handling. Inputs: 834 EDI (005010X220A1), CSV, flat files, HRIS exports and API payloads, received over SFTP, webhook or API. Senders keep their existing format and layout, and each source is mapped to one member model. Validation: every record is checked for field type and range, duplicates, consistency across a member's records, and deviation from the prior file. A change threshold catches file-wide problems such as an unintended mass termination. A failed record is held on its own while the rest of the file continues; a file-wide error stops the file. Corrections are added to that source's validation rules. Exception handling: Dart's specialists set up each feed, review failed records, and update mappings when an employer changes systems. Software suggests the likely cause of an error, and a person decides the resolution. Identity and history: members are matched across eligibility, claims, leave and program files. Dart reports a match rate above 99% across roughly 3 million records a month, with uncertain matches routed to a person. Change history is kept within a configurable lookback window for auditing. Outputs: JSON over REST for eligibility, claims, leaves, members, programs and program enrollments, with direct member updates through the API. Pro and Enterprise tiers add configurable output and custom input transformations. Results: Dart reports new feeds go live in under 7 days. Handpicked Health used Data Nexus to launch a Fortune 50 employer in weeks rather than a typical six-month implementation, and now brings on new Fortune 50 feeds in under 24 hours. Typical customers: digital health companies with 20 to 500 employees that sell to employers, such as MSK, mental health, oncology navigation, GLP-1 and cardiometabolic, fertility, caregiving and leave management providers. Not designed for: real-time 270/271 payer eligibility checks, ben-admin-to-carrier enrollment, claims analytics, embedded CSV importers or HL7/FHIR EHR integration. Security: HIPAA compliant, SOC 2 Type II audited, encrypted in transit and at rest, BAAs signed; reports available in Dart's Trust Center. Pricing: monthly subscription in Validation, Starter, Pro and Enterprise tiers based on feeds and monthly record updates, starting at $4,990 per month on a one-year term; a $2,990 per month paid pilot covers up to 3 feeds.

Datuum.ai

Datuum is a no-code platform that uses AI to seamlessly integrate your data into any destination in a matter of minutes. Our platform is designed to simplify data integration for professionals of all levels by creating resilient connectors to various data sources, automatically discovering data, and mapping it to the final destination without any coding required. With Datuum, you can create a self-service onboarding experience for your customers and accelerate data operations, freeing up time to focus on insights that drive growth. Whether you're a seasoned data professional or a newcomer to the field, Datuum makes data management easier and more efficient.

DBF Comparer

DBF Comparer is a safe and easy to use tool that IT specialists and casual users of DBF database files alike will find absolutely indispensable.

DBMoto

DBMoto software makes it easy to implement heterogeneous Data Replication, Change Data Capture, and Data Transformation capabilities — without the need for consulting services. It supports all major databases including IBM DB2 (including i/AS400, LUW and z/OS).

Average Rating: 4.3/5.0

Total Reviews: 2

DBSoftlab

DBSoftlab is a software company specializing in data transformation and migration solutions. Their flagship product offers a comprehensive toolkit designed to facilitate seamless data migration across a wide array of database systems and file formats. With a focus on simplicity, efficiency, and speed, DBSoftlab aims to make complex data integration tasks accessible to users of varying technical expertise. Key Features and Functionality: - Extensive Migration Support: The toolkit supports over 256 migration methods, enabling data transfer between numerous platforms, including Oracle, SQL Server, MySQL, MariaDB, PostgreSQL, IBM DB2, Informix, Teradata, MS Access, MS Excel, Visual FoxPro, SQLite, Firebird, InterBase, dBase, Paradox, Lotus, CSV, Text Files, Mailbox, HTML, and any ODBC DSN. - User-Friendly Interface: A step-by-step wizard-driven GUI simplifies the migration process, allowing users to complete data transfers in just three steps without requiring advanced technical skills. - High Performance: The toolkit is optimized for speed, ensuring rapid data migration even with large datasets. - Comprehensive Data Handling: It manages large objects (LOBs, primary keys, indexes, foreign keys, default values, and auto-increment fields, while also supporting schema migrations across different database systems. - Customization and Flexibility: Users can modify table and field names, data types, lengths, default values, and apply data filters during the migration process. - Global Compatibility: The toolkit supports UNICODE and automates character set conversions between different encodings, such as UTF-8, LATIN, CP1250, and ASCII. Primary Value and User Solutions: DBSoftlab's migration toolkit addresses the challenges associated with data integration by providing a powerful yet easy-to-use solution for transferring data between diverse systems. It eliminates the need for manual data entry or complex scripting, reducing the risk of errors and saving valuable time. By supporting a wide range of databases and file formats, the toolkit ensures that organizations can maintain data consistency and integrity during migrations, facilitating smoother transitions and more efficient data management.

Definite

Definite is an all-in-one data analytics platform that combines a managed data warehouse, ELT pipelines, semantic layer, and business intelligence in a single product. Teams connect data sources using 500+ pre-built connectors for CRMs, payment platforms, marketing tools, databases, and spreadsheets. Definite automatically ingests, stores, and models the data in a managed data warehouse powered by DuckDB. Users analyze data and build dashboards using Fi, an AI-powered analytics assistant. Fi translates natural language questions into SQL queries and returns visualizations, summaries, and insights without requiring technical expertise. Key capabilities: - Managed cloud data warehouse - 500+ pre-built data connectors and ELT pipelines - Semantic layer for reusable metrics and data modeling - AI-powered natural language querying (no SQL required) - Interactive dashboards and data visualizations - Automated reporting to Slack, email, and Google Sheets - Embeddable analytics and white-label dashboards Built for: Startups, small businesses, and lean data teams who need modern data analytics without managing a complex stack of tools like Snowflake, Fivetran, dbt, and Tableau.

Average Rating: 4.0/5.0

Total Reviews: 1

Delman

Connect and unify your data from a combination of files, databases and apps, with just a few clicks.

DigiData

DigiData connects the business software European SMEs already use (Exact Online, Twinfield, AFAS, Nmbrs, Moneybird, Simplicate, Bouw7, HubSpot, Pipedrive, Stripe, Shopify and 30+ more) and syncs it into a dedicated PostgreSQL database per customer. From there teams get ready-made dashboards, an OData feed and CSV export for Power BI and Excel, an AI agent that answers questions about their own numbers, and a read-only MCP server for ChatGPT and Claude. Admins control access per source, table and column; there are no write tools and no arbitrary SQL, and data is stored in the EU.

DLRunner

DLRunner is a Salesforce Data Loader automating data loader jobs and archiving.

Document Lens

Document Lens is an advanced tool designed to recognize and extract entities from text files in PDF, DOCX, and TXT formats. Utilizing a scalable Natural Language Processing (NLP pipeline, it efficiently retrieves entities from multi-domain knowledge graphs or datasets accessible via SPARQL endpoints. This capability enables users to transform unstructured documents into structured, actionable data, facilitating seamless integration into various data processing workflows. Key Features and Functionality: - Entity Recognition and Extraction: Identifies and extracts entities from text documents, converting unstructured data into structured formats. - Multi-Format Support: Processes documents in PDF, DOCX, and TXT formats, ensuring versatility across different document types. - Scalable NLP Pipeline: Employs a robust NLP pipeline that can be configured to retrieve entities from diverse knowledge graphs or datasets via SPARQL endpoints. - Configurable Options: Offers a range of configurable settings, allowing users to tailor the tool to specific requirements and data sources. - Integration Capabilities: Designed to function as part of a larger end-to-end system, integrating seamlessly with other data processing tools and workflows. Primary Value and Problem Solved: Document Lens addresses the challenge of extracting meaningful information from unstructured text documents. By automating the recognition and extraction of entities, it significantly reduces the time and effort required for manual data processing. This automation enhances data accuracy and consistency, enabling organizations to efficiently integrate valuable information into their data ecosystems. As a result, users can make more informed decisions, streamline operations, and unlock insights from previously inaccessible data sources.