Wer nutzt diese Software?
Unternehmen und mittelständische Unternehmen in einer Vielzahl von Branchen wie Finanzen, Gesundheitswesen, Einzelhandel und mehr.
Durchschnittliche Bewertung95 Bewertungen
- Gesamt 4.3/5
- Benutzerfreundlichkeit 4.4/5
- Kundenservice 4.6/5
- Funktionen 4.1/5
- Preis-Leistungs-Verhältnis 4.1/5
- Kostenlose Version Ja
- Gratis Testen Ja
Cloud, SaaS, Web
24/7 (Live Vertreter)
Angaben zum Hersteller
- Gegründet 2011
Matillion bietet das einzige Datenumwandlungsprodukt, das speziell für Cloud-Data-Warehouses entwickelt wurde. Diese Lösung bietet:
1) Extrahieren und Laden von Geschäftsdaten in eine CDW, um den Umfang und die Leistung bereitzustellen, die für datengesteuerte Analysen erforderlich sind.
2) Die Fähigkeit, durch diese leistungsstarken Transformationsfunktionen verschiedene Datenquellen eines Unternehmens zusammenzuführen und den Prozess abzuschließen, um Daten vollständig analysefähig zu machen.
- Match & Merge
- Nichtrelationale Transformationen
Die hilfreichsten Reviews für Matillion
Bewertet am 13.6.2019
Agile Data Engineering
Kommentare: We use Matillion to produce highly curated datasets for customers. Matillion has allowed us to move this workload entirely into the data warehouse where the final work product lives, and cut processing time from days to hours.
Vorteile: Matillion allowed us to move a legacy ETL pipeline to BigQuery with speed, precision, and confidence. It is now used exclusively by our team for all of our ELT needs. The user interface is clean, intuitive, and allows members of the team to be immediately productive. Onboarding new users has never been easier.
Nachteile: Feature parity between the different flavors (Redshift, Snowflake, BigQuery) is lacking, however, Matillion continues to make progress in narrowing the gap.
Bewertet am 14.6.2019
Easy to use solution, allowing rapid delivery of ELT processes
Kommentare: We came to Matillion while looking for a tool that would allow us to orchestrate our load processes for Amazon Redshift. We'd used other ETL tools previously, were blown away by how easy it was to pick up and understand Matillion. We liked the simplicity, and the fact that we could always dig into the SQL that was generated. New features are added frequently, and we usually find one or two improvements that directly impact us with each release. Their support team are also very responsive, and Matillion are always keen to help you get the most out of their software, so there's a lot of support if you want it. 2+ years later, and we're using Matillion to run all our ELT jobs across various data warehouse projects, and very happy with it.
- Very intuitive design environment - super quick to learn.
- Components map closely to SQL capabilities in Redshift.
- Easy to view the SQL generated.
- Sample, row count, and data lineage make it easy to unit test as you build.
- Powerful management options via REST API (orchestration, Github integration, etc.).
- Native AWS integration.
- Aggressive release cycle, constantly adding new features.
- Easy to document in-workflow.
- Lots of third party integrations.
- User concurrency/licencing model (simple, but can't be customised to fit your need).
- Exception handling could be improved.
- A single Task View would be helpful for multi-environment/project support.
Bewertet am 14.6.2019
Need on the fly connectivity to different instance of Redshift
Vorteile: I like the bunch of API integrated in Matillion it helps me to directly grab the data from different sources without manually extra and import in my database.
Nachteile: I am using Matillion for Redshift from last more than 2 years. When i setup a project in Matillion with connection to a Redshift cluster, sometimes there is a need to extract the data from other instance of Redshift while running job in Matillion. In that case there is straight forward way of getting the data from other instance of Redshift like you have comments to extract the data from databases like SQL Server, Oracle etc. instead of first i need to run another job by connection second Redshift cluster and extract the records after that run different job to load the extracted records from S3 to main Redshift cluster.
Bewertet am 13.6.2019
Responsive to User Needs
Kommentare: Gets better and better with each release. Keep up the good work!
Vorteile: I've been using Matillion for about 2 and a half years. I've seen the software improve so much in that time. If I ever found a feature to be lacking, it would be included within the next couple release cycles. The software really seems to adapt as user needs have been evolving. Some of my favorite recent features are the ability to configure some components with just text (really saves me time) and the many Grid orchestration components which allow me to greatly reduce the complexity of the orchestration jobs.
UX is sometimes lacking or inconsistent. For example, let's say my goal is to replace an existing job with a new job of the same name. I delete the old job, and import the new one with the same name. All Orchestration components that used that job will understand to use the new job, but for some reason the scheduler doesn't.
Also, jobs will have validation errors simply because the components haven't been validated (grey borders). It can be confusing because you may be searching for an error in your work when all you actually have to do is revalidate the job.
Bewertet am 13.6.2019
Great for pipelining data to warehouse/lake, not getting it back
Kommentare: It was easy to get set up, and it worked great for pushing data into Snowflake as a data warehouse. However, we quickly realized that we would need yet another tool to get the data back out to the source systems to synchronize/integrate it. We could sort of do it with Matillion, but it required a lot of custom programming and was not very intuitive. We ended up using a different iPaaS tool that could handle traffic/integration in both directions.
Vorteile: It is extremely fast and easy to pull data from various sources and pipe it into Snowflake. The graphic interface lets this happen without programming.
Nachteile: There is almost no ability to get data back from your warehouse into the other systems to synchronize the data. It's great to have it all in the warehouse, but it seems pretty critical to have that data flowing back to other systems that are part of your environment. The pricing model is frustrating. You are billed for when the machine instance is ON, not when it is actively doing something. So, if you have a couple hours of job that run in a day, you have to shut down the machine to save money the rest of the day. With it shut down, development can't happen. So, we had to turn it on and off all the time. It would be much better if they billed as it is used, not as it is on.