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Dataddo

Dataddo

IT Services and IT Consulting

Praha 8, Prague 4,947 followers

No-code data integration platform that lets users get data to wherever it needs to go - dashboards, warehouses, or apps.

About us

Dataddo is a fully-managed, no-code data integration platform that connects cloud-based applications and dashboarding tools, data warehouses, and data lakes. It offers 3 main products: - Data to Dashboards, which lets users send data from online sources straight to dashboarding apps like Tableau, Power BI, and Google Data Studio for insights in record time. A free version is available for this product! - Data Anywhere, which enables users to send data from any A to any B—from apps to warehouses or dashboards (ETL, end to end), between warehouses (ETL), and from warehouses back into apps (reverse ETL). - Headless Data Integration, which allows enterprises to build their own data products on top of the unified Dataddo API and get all integrations in one. The company’s engineers manage all API changes, proactively monitor and fix pipelines, and build new connectors free of charge in around 10 business days. The platform is SOC 2 Type II certified and compliant with all major data privacy laws around the globe, including ISO 27001. From first log in to complete, automated pipelines, get your data flowing from sources to destinations in just a few clicks.

Industry
IT Services and IT Consulting
Company size
11-50 employees
Headquarters
Praha 8, Prague
Type
Privately Held
Founded
2015
Specialties
Data integration, Data extraction, Data federation, Analytics, ETL, Data automation, Data architecture, Process automation, Data fabric, and No-code platform

Products

Locations

Employees at Dataddo

Updates

  • Dataddo reposted this

    The EU's new Cloud and AI Development Act (CADA) is fundamentally shifting the enterprise IT playbook. We are moving away from an era of unchecked reliance on global hyperscalers and location-agnostic cloud setups. Under these new rules, tech sovereignty is no longer just a legal checklist item; it is becoming a foundational architectural requirement that mandates localized control, data portability, and strict vendor independence. For organizations to remain competitive and compliant, data architectures must now be intentionally designed around heterogeneous environments and infrastructure isolation. This massive industry shift directly mirrors the vision we’ve always had at Dataddo, where we built our platform to natively support true on-prem and hybrid deployments to give businesses absolute autonomy over their data. As the regulatory landscape evolves toward a sovereign-by-design future, maintaining this level of architectural flexibility will be critical. #TechSovereignty #CADA #DataArchitecture

  • We loved having the Prague PostgreSQL Meetup community over in April, so we're doing it again! 🐘 The Prague PostgreSQL Meetup Summer Special is back at Dataddo HQ. Same good crowd, new talks, and yes... food and cold drinks are on us (it's a Monday evening, after all). 📅 Monday, June 1, 2026 | 17:30 📍 PORT7, Building E3, 7th Floor, Pod Dráhou 1637/6, Prague Three speakers, three deep dives: 🔹 Laurenz Albe: Security attacks on PostgreSQL 🔹 Ants Aasma: We have the explain, now what? 🔹 Josef Šimánek : Terabyte-Scale PostgreSQL on custom HW/Infra If you were at our April edition with Artjoms Iškovs and Andreas Scherbaum, you know the vibe. If you missed it, this is your chance. Practical talks. Good conversations. Cold drinks and food taken care of. 🎟️ RSVP: https://lnkd.in/dZTFKG9x #PostgreSQL #Dataddo #Prague #TechMeetup #Database #OpenSource

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  • Not all workflows need a landing zone between source and tool. With any of our 400+ connectors, you can now stream data directly into your notebook, dashboard, or app - no intermediate storage, no extra parsing and latency. Our founder's DMs are open if you want to dig in.

    For years, standard data pipelines have forced one approach: extract from the source, land a copy in a data lake or warehouse, and then let the consumer query it. But what if you had the choice to skip that intermediate step entirely, e.g., for bringing the data directly to your Jupyter notebook, dashboarding app, or Claude? I am thrilled to announce that Dataddo can now serve data directly to your downstream tools in Apache Arrow format! This is now supported by all of our connectors. We aren't saying you should always bypass your DWH / Data Lake / Lake House, this absolutely still has its place. But now, we are giving you the more flexibility to choose. For use cases where you need lightning-fast access without intermediate storage costs or the "Serialization-Deserialization Compute Tax" our connectors can stream data directly into your consumer’s memory. That means no landing zones, no pipeline latency, and no duplicate files to govern, unless you actually need them. Ping me a DM in case you want to know more. #DataEngineering #ApacheArrow #DataArchitecture #ZeroCopy #DataPipelines #Dataddo #DataLakehouse

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  • The questions data leaders are asking at summits like this are exactly what shape our roadmap at Dataddo. Managing millions of data flows daily gives us a front-row seat to what's breaking, what's working, and where the real gaps are in production (not just theory). If you're at #GartnerDA and want that perspective in the room, our friendly founder has fresh opinions to share.

    The Gartner Data & Analytics Summit in London kicks off today, and I’m looking forward to diving into the sessions on the evolving data landscape. As we scale Dataddo, I always find these summits to be the best place to hear what’s actually keeping data & AI leaders up at night. If you're here and want to catch up for 15 minutes over a coffee, drop me a DM and I’d love to hear what’s on your roadmap for 2026. #Gartner #Data #AI #Networking

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  • View organization page for Dataddo

    4,947 followers

    In Prague on Monday? Your plan is: #PostgreSQL & cold drinks with the best engineers🐘 We’re bringing together the local #PostgreSQL community and amazing speakers for a night of real-world talks and relaxed networking at the Dataddo office.  🔷 Artjoms Iškovs: Postgres & Data Lakes.  🔷 Andreas Scherbaum: WarehousePG & Open Source.  🔷 Gülçin Yıldırım Jelínek & Juraj Slota: Intro & Opening  📅 Monday, April 27 | 17:30  📍 Dataddo: Holešovice, PORT7, building E3 - 7th Floor  🎟️ RSVP now: https://lnkd.in/gfx8Sksx

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  • 𝐃𝐚𝐭𝐚 𝐔𝐭𝐢𝐥𝐢𝐭𝐲 + 𝐃𝐚𝐭𝐚 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲? At Dataddo, we know the "PII headache." 🤕 Data moves from sources to warehouses, dashboards, and AI pipelines—and every hop adds a layer of regulatory and reputational risk.📉 Most teams solve this with tedious manual workflows downstream. We decided to fix it at the root.🛠️ 🛡️Introducing: Enhanced Data Masking at the Source. We’ve made it possible to anonymize sensitive fields before they ever leave the source system. • 🔍 Auto-Detection: No more manual mapping. Our system finds the PII for you. • 🔐 Irreversible Hashing: One-way masking ensures data stays anonymous. • 🧂 Custom Salts: Unique hashing contexts for every customer for maximum security. The Result? You get the full power of all your data in your AI workflows—without the nightmares. 🚀 Check it out here: https://lnkd.in/d4FJnYa2 #DataEngineering #AISafety #DataPrivacy #Dataddo #FinTech

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  • Dataddo reposted this

    Amazon Web Services (AWS) recently published a nice piece on building open data lakes with Apache Iceberg and Dataddo. With Dataddo you can land data directly into Iceberg tables and use Glue as the central layer to manage everything — simple, and it just works. Iceberg is quickly becoming a go-to format for modern data lakes, mainly because it brings reliability and interoperability without forcing you into a specific stack. I’ll drop the link in the comments — worth a read if you’re working with AWS and thinking about where your data architecture is heading. #Dataddo #AWS #ApacheIceberg #DataEngineering

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  • View organization page for Dataddo

    4,947 followers

    𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 𝐢𝐬 𝐞𝐚𝐬𝐲. 𝐔𝐧𝐭𝐢𝐥 𝐢𝐭 𝐢𝐬𝐧’𝐭. Modern enterprises run on hybrid architectures, dozens of cloud services, and hundreds of data sources. Connecting everything to Amazon Web Services (AWS) often means building and maintaining fragile pipelines. That’s exactly the challenge we built Dataddo to solve. In this AWS Partner Network article, we show how organizations can: • Centralize data from hundreds of sources into AWS • Build ETL, ELT, reverse ETL, and replication pipelines without heavy engineering • Keep pipelines running even when APIs and schemas change • Deliver data to analytics teams faster If you’re building data infrastructure on AWS, this article shows a practical architecture for unifying fragmented systems. Read the full article on the AWS blog: https://lnkd.in/ef2fgep5 #DataIntegration #AWS #HybridCloud #DataEngineering #Dataddo

  • View organization page for Dataddo

    4,947 followers

    🔍 Enterprise AI v roce 2026: bez kvalitních dat to nepůjde Mnoho organizací při nasazování AI agentů naráží na stejný problém: data nejsou připravená. Společně s našim partnerem BigHub proto chystáme webinář, kde se podíváme na to, co v praxi rozhoduje o úspěchu (nebo neúspěchu) AI iniciativ. Konkrétní tipy a příklady z reálných projektů a use-casů, bez teorie. 👉 kde firmy nejčastěji chybují při budování datových pipeline pro AI 👉 praktické kroky pro integraci dat z různých firemních systémů 👉 reálné příklady nasazení AI agentů nad kvalitními daty 📅 12. 2. 2026 | 10:00 - 11:00 ✅ Registrace zdarma: https://lnkd.in/dChDQihR

    View organization page for BigHub

    1,582 followers

    Vedete ve firmě data nebo AI a řešíte, jak posunout AI z plánů a pilotů do produkce? Ve spolupráci s Dataddo vás zveme na webinář: Jak připravit firemní data pro AI v roce 2026. 📅 12. 2. 2026 | 10:00 - 11:00 🎥 On-line, Microsoft Teams Prezentovat budou: - Karel Šimánek (Co-founder & CEO, BigHub) - Petr Nemeth (Founder & CEO, Dataddo) Žádná obecná teorie, ale konkrétní tipy z praxe a reálných projektů. Probereme prakticky, co je potřeba mít vyřešené, aby AI dávala konzistentní výsledky a šla škálovat napříč use-casy a celou organizací. 🎯 Pro koho: CIO, CTO, CDO, Head of Data/AI a další decision-makeři v této oblasti z velkých a enterprise firem ✅ Registrace zdarma: https://lnkd.in/dhcuNQuJ

  • View organization page for Dataddo

    4,947 followers

    🔵 + 🟣 = 🖼️ 📊🫰 We love seeing this live! Databox's new ingestion API + Dataddo’s connector ecosystem makes unified (and beautiful!) reporting easier than ever, for teams of all sizes.

    View profile for Peter Caputa

    It's now possible to visualize any data from any tool in Databox. Part of the reason why Databox is so easy to setup is that we have built and we maintain 100+ deep integrations with popular tools that make it easy. Once we build a native integration with a tool like HubSpot, Google Ads, Youtube, Quickbooks, etc, etc, the dashboard and report setup process process becomes simple for a Databox user: 1️⃣ Connect via OAuth (all you need is your id and password)  2️⃣ Select from a list of pre-built metrics specific to each integration and add them to a dashboard, report, scorecard, set a goal, build a forecast model, etc, etc.  3️⃣ Browse pre-built dashboard and report templates which include groups of metrics in the visualizations you'd expect. In other words, you can have live dashboards in minutes. This is in stark contrast with typical business intelligence tools that require hours, if not days, of a developer’s or analyst’s time. We wish we could build a native integration with every tool out there. But, we do not have the resources to build every integration that every customer could want. In the past, we had an API that allowed a customer to push in data for one metric at a time (a value, a time stamp and a dimension). This was limiting for a variety of reasons:  ➡️ They'd have to write and host code that pulled data from APIs and formatted it the way our system required. ➡️ They'd have to write code for every metric they wanted to track.  ➡️ If something changed in the way a customer stored their data, they'd have to update their 3rd-party code. Our new ingestion API (https://lnkd.in/eFhFGknk) eliminates these limitations. It does this by allowing our customers to push us tables of data. You can still write and host your own code to pull the data from another system and send it into Databox. But, the smarter thing to do is to use an ETL tool. (Stands for Extract, Transform, Load.) As part of launching this new API, we have also launched a partnership with Dataddo (https://lnkd.in/e-R9bTmj). Dataddo makes it easy to pull data in from any system and push it out to any destination. They’ve also built connectors with 300+ SaaS tools with plans to have 450 by the year's end, which makes the authentication process very quick and easy, just like in Databox. Once you push the data into Databox via our ingestion API or from Dataddo, you can then filter and merge datasets, calculate new values and build metrics that can be used on dashboards, reports, scorecards, as goals, etc. We'll continue to maintain and build new integrations for the most popular SaaS tools and services, in order to make setting up dashboards and reports as easy as possible. But with our new ingestion API, tools like Dataddo can help our customers push data into Databox from anywhere.

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Funding

Dataddo 5 total rounds

Last Round

Series unknown

US$ 1.4M

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