InetSoft's BI platform, StyleBI, enables users to seamlessly extract data from multiple sources, and create dashboards and automated reports that reveal advantageous insights. The robust data mashup engine can join many data sources on common dimensions so that an aggregation of sources can be analyzed and manipulated within a single view. Once IT has connected and defined data sources, everyday users can create sophisticated reports and impressive visual analytic dashboards.
InetSoft's data extraction tools are capable of simultaneously accessing and integrating information from operational databases, data warehouses, and enterprise applications.
Listed below are the more commonly used data sources that have JDBC/ODBC connectors plus the non-ODBC sources for which InetSoft has native connectors already built.
| 42Matters | Actian Vectorwise | ActiveCampaign |
| Adobe Analytics | AirTable | Airtable Dashboard |
| Amazon Aurora | Amazon Redshift | Apache Cassandra |
| Apache Spark | App Annie | appFigures |
| Asana | AskNicely | Baan Infor |
| Bitly | box | Buffer |
| Campaign Monitor | Chargebee | Chargify |
| ChartMogul | Cloudera | Copper |
| CSV | Data.Gov | data.gov |
| Data.world | Derby | EMC Greenplum |
| FileMaker | Firebird | |
| Flat files | FreshBooks | Freshdesk |
| Freshworks CRM | Freshservice | Fusebill |
| Google AdSense | Google AdWords | Google Analytics |
| Google Analytics | Google Calendar | Google Search Console |
| Google Sheets | GoSquared | Hadoop/HIVE |
| Harvest | Help Scout | HP Vertica |
| Hubspot | Hyperion ESSbase | IBM DB2 |
| IBM Netezza | Informix | Infusionsoft |
| Ingres | Insightly | Intervals |
| Intuit QuickBooks | Java beans (POJO) | JDBC |
| Jira | Keen | Kissmetrics |
| Lighthouse | LiveAgent | Mailchimp |
| MapR | Microsoft Access | Microsoft Excel |
| Microsoft SharePoint | Microsoft SQL Server | Microsoft SQL Server Analysis Services |
| monday.com | MongoDB | MySQL |
| New Relic | Nicereply | OData |
| ODBC | Optimizely | Oracle |
| Oracle Hyperion | Oracle JD Edwards | Oracle OBIEE |
| Oracle PeopleSoft | ParAccel | ParStream |
| Pervasive | Pipedrive | PipelineDeals |
| PostgreSQL | Progress | Prometheus |
| QuickBooks Online | QuickBooks Payments | Recurly |
| REST | Salesforce | Salesforce Reports |
| salesforce.com | SAP ERP | SAP HANA |
| SAP NetWeaver | SAP NetWeaver Business Warehouse | SAP SQL Anywhere |
| Sendible | SEOmonitor | ServiceNow |
| Siebel CRM | Smartsheet | Snowflake |
| SOAP | SparkPost | SQLite |
| Stripe | Survey Monkey | SurveyGizmo |
| Sybase ASE | Teradata | Toggl |
| Twilio | Twilio SendGrid | Web Services |
| Wistia | WordPress | XML |
| YouTube | Zapier | Zendesk |
| Zendesk Sell | Zoho CRM |
Many supported, less common data sources are not listed. Custom data connectors can also be built by you or InetSoft.
A regional logistics firm switched because it needed lower total cost of ownership and faster dashboard delivery. The team also wanted stronger embedding APIs for white-labeled tenant experiences without heavy middleware. StyleBI cut dashboard build time in half by enabling reusable templates and simpler theming controls. The company reduced platform and cloud costs significantly while lowering support tickets tied to embedded analytics. Customer adoption of embedded dashboards increased because performance and onboarding improved after the migration.
A SaaS company moved to StyleBI to reduce rising licensing and infrastructure costs while supporting multi-tenant analytics. They needed lightweight embedding with direct product integration rather than fragile iframe-heavy mashups. StyleBI helped them shorten dashboard development cycles through templates and reusable components. The operations team benefited from lower maintenance overhead and faster upgrades. The business also gained better renewal support because customer-facing analytics became easier to deliver and brand.
The manufacturer sought a platform that could handle embedded analytics and role-based operational views more naturally than its prior setup. It needed direct connectivity to multidimensional and relational data without creating many intermediate extracts. StyleBI provided interactive drill-down analysis from KPI level to batch-level production details. The open source positioning improved cost efficiency for broader departmental rollout. Teams gained a more practical balance of flexibility, usability, and data depth for day-to-day manufacturing decisions.
The company switched to gain better scalability and performance across production and supply chain analytics. It also needed easier integration between legacy ERP systems and real-time plant data sources. InetSoft enabled more tailored dashboards for plant, quality, and executive stakeholders. Embedded access in the internal portal improved usage for non-technical users who needed immediate insight. After the transition, the manufacturer reported faster reporting cycles and stronger operational visibility.
The processor moved because it needed web-first embedded dashboards that operators and managers could use without SQL dependence. Rising licensing pressure and dashboard complexity also made the previous approach less sustainable. StyleBI let the team blend ERP, quality, sensor, and production data with less ETL overhead. Real-time KPI visibility improved reactions to moisture, yield, and contamination deviations on the floor. The organization reported stronger adoption, better traceability, and more consistent production quality outcomes.
The firm selected StyleBI to better align analytics with high-frequency plant operations and reduce total ownership costs. It required embeddable dashboards inside existing operational systems so users could act without context switching. InetSoft offered a lighter deployment footprint and a licensing model that fit mixed technical and operational audiences. Programmatic control and server-side mashups improved the speed of dashboard iteration and issue response. The business realized stronger plant-floor adoption and measurable improvements in process efficiency and margin sensitivity.
The manufacturer switched because component-level visualization was no longer enough for broader analytics and reporting demands. It needed self-service access for non-technical teams and scalable distribution of operational reports. InetSoft provided a unified BI stack for data mashups, dashboard authoring, and controlled embedding into existing portals. The phased migration approach reduced risk while validating KPI consistency and performance under live load. Benefits included better traceability, lower development overhead, and stronger customer-facing transparency.
The company switched to support faster operational insight into plating, porosity, yield, and quality conditions. Oracle BI delivered reporting depth, but the team wanted a more agile and embeddable platform for production workflows. StyleBI enabled real-time mashups across sensors, ERP records, and lab outputs with improved responsiveness. Engineers and operators could iterate dashboards faster and detect process drift earlier. The move delivered better cross-team visibility, reduced overhead, and more proactive quality control.
The mining organization needed to move beyond SQL-heavy dashboards that limited access for non-technical users. It also needed richer interactivity and better performance across Redshift, RDS, and S3-backed analytics workloads. InetSoft was chosen for AWS-friendly integration, data mashup flexibility, and more usable visual exploration. Teams gained faster decisions through auto-refreshing dashboards and interactive filtering across sites and equipment. Adoption expanded materially while IT spent less time on manual report maintenance.
The refurbisher switched because static ERP dashboards were not enough for complex, compliance-heavy supply chain operations. It needed multi-source integration across ERP, manufacturing, logistics, and quality systems in one analytical view. StyleBI delivered role-based interactive dashboards with drill-through analysis and proactive alerting. This improved the ability to identify bottlenecks, forecast delays, and maintain traceability for regulated components. The company gained faster reporting, stronger compliance readiness, and clearer ROI from supply chain optimization.
The manufacturer changed platforms because spreadsheet-centered workflows were too rigid for cross-functional financial intelligence. It needed richer visualization, broader integration with operational systems, and better scalability as data volumes grew. StyleBI enabled self-service dashboards for finance, engineering, and operations while reducing manual consolidation work. Automated refresh and drill-down capabilities improved planning speed and financial transparency. The result was a more data-driven culture with lower licensing pressure and stronger decision support across departments.
The specialist migrated to overcome single-source and static-report limitations that constrained production and R&D insight. It required a platform that could mash up instrument, ERP, CRM, and quality data for deeper analysis. InetSoft provided interactive, scalable reporting that supported drill-down and faster cross-team collaboration. IT overhead dropped because centralized self-service dashboards replaced repeated custom template maintenance. The company achieved quicker reporting cycles, better operational alignment, and improved customer transparency.