기업의 더 효율적인 소프트웨어
선택을 위한 17년 지원 경험
Datalore은(는) 무엇인가요?
Datalore Enterprise는 팀을 위한 데이터 과학 노트북 플랫폼입니다. 브라우저에서 작동하고 Jupyter와 호환되는 Datalore Enterprise는 Python, SQL, R 및 Scala 노트북을 위한 스마트 코딩 보조 기능을 제공합니다. 팀에서 링크를 통해 노트북을 공유하고, 실시간으로 공동으로 편집하고 작업 공간에서 프로젝트를 관리할 수 있습니다. S3를 지원하는 Datalore Enterprise는 편집기에서 직접 SQL 데이터 소스에 연결할 수 있습니다. 연구 결과를 공유하기 위해 데이터 과학자는 노트북을 보고서로 전환하고 이를 이해 관계자들과 공유할 수 있습니다.
Datalore은(는) 누가 사용하나요?
Datalore Enterprise는 Python, SQL, R 또는 Scala에 집중되어 있고 비공개 클라우드 또는 온프레미스 환경에서 데이터 과학 플랫폼을 호스팅하려는 데이터 과학 및 데이터 분석 팀을 위해 설계되었습니다.
Datalore은(는) 어디에 배포할 수 있나요?
공급업체 정보
- JetBrains
- 설립 연도: 2000
Datalore 지원
- 채팅
언어
영어
공급업체 정보
- JetBrains
- 설립 연도: 2000
Datalore 지원
- 채팅
언어
영어
Datalore 동영상 및 이미지
Datalore 특징
Datalore 리뷰
It will help a lot in your company
주석: I'm very satisfied with the product, always tell about when I meet people that works as data analysts.
장점:
The features i mostly use is being able to schedule your notebooks, saving them in the cloud, being able to share a link to people that can help you in real time and the jetbrains algorithm to help me write my code. These features make my work very easier since I don't have to worry about running the scripts or setting up an airflow server.
단점:
Sometimes the kernel will just bug and you'll have to restart it but it never happens on scheduled notebooks and if it bugs you can always restart it with the click of a button so it's not annoying at all, and it happens very few times.
Datalore for myself
주석: It is good, especially for package management and reporting
장점:
Easy to manage python packages, it saves a lot of time
단점:
Fine grade permission management on sharing notebooks and reports, I think most enterprise companies require this
고려된 대안: Looker
Datalore 선택 이유: Audit control issue, dashboard issue
Datalore 전환 이유: Internal requirements, audits, permission control and so on
Good tool but occasionally unreliable
주석: God, but they need more storage space... and make sure that files over the storage limit can somehow be retrieved even if for a short while.
장점:
Ability to work across windows and mac environments; working in the cloud provides reliability and peace of mind... which is not the case with personal machines.
단점:
I lost data; Looks like, if the size is large, it doesn't back up the data... and there is no way to access it. I did these analysis that took like 30 hours of computing. It was a jsonl file; when I tried to get it into csv format, since the files were so large, it never saved anything. Proved to be a waste of time.
Incredibly useful jupyter-like environment
주석: I love datalore - it's made my life so much easier, taking care of the tasks I normally dread like setting up remote machines or scheduling tasks. And if you come from the pycharm environment, you won't be missing the top notch code completion functionality. It's also great that signing up to it with a free account is easy and seamless for people I want to share notebooks with (I am on the professional tier)
장점:
Really easy and intuitive environment which makes settting up, sharing and collaborating on apps a breeze. Great for very quick prototyping. Their chron feature is fantastic too. Code completion is excellent.
단점:
I wish I could integrate with local files better in a programmatic way, rather than having to upload them manually.
GP uses Datalore
장점:
- option to use GPU- performance tiers- very fast
단점:
- some of the visuals does not work properly (graphviz)- Dash cannot be open separately for preview, needs to be saved instead- profile does not remember installed API, each machine restart requires to reinstall them