--- description: 검증된 사용 후기를 확인하고 Databricks 사용성, 특징, 가격, 장점과 단점에 대한 자세한 정보를 확인해보세요! 비슷한 경쟁 제품도 확인이 가능합니다. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: Databricks 가격, 사용 후기, 평점 | 켑테라 Capterra --- Breadcrumb: [홈](/) > [빅 데이터 소프트웨어](/directory/30851/big-data/software) > [Databricks](/software/148499/databricks) # Databricks Canonical: https://www.capterra.co.kr/software/148499/databricks Page: 1 / 2\ 다음: [Next page](https://www.capterra.co.kr/software/148499/databricks?page=2) > 빅 데이터 처리 및 시각화를 더 간편하게 수행할 수 있도록 지원하는 데이터 과학 팀을 위한 클라우드 기반 분석 플랫폼입니다. > > Verdict: Rated **4.5/5** by 23 users. Top-rated for **추천 가능성**. ----- ## Overview ### Databricks은(는) 누가 사용하나요? AI 및 기계 학습을 통해 데이터 과학, 엔지니어링 및 비즈니스 워크플로를 단일 플랫폼으로 통합하여 기업이 실행 가능한 통찰력을 이끌어낼 수 있도록 지원하는 클라우드 기반 데이터 분석 플랫폼입니다. ## Quick Stats & Ratings | Metric | Rating | Detail | | **종합** | **4.5/5** | 23 리뷰 | | 사용 편의성 | 4.7/5 | Based on overall reviews | | 고객 지원 | 4.4/5 | Based on overall reviews | | 비용 대비 가치 | 4.2/5 | Based on overall reviews | | 특징 | 4.6/5 | Based on overall reviews | | Recommendation percentage | 90% | (9/10 추천 가능성) | ## 공급업체 정보 - **회사**: Databricks - **Founded**: 2013 ## Commercial Context - **시작 가격**: US$99.00 - **Pricing model**: (Free version available) (무료 체험판) - **Target Audience**: 자영업, 2~10, 11~50, 51~200, 201~500, 501~1,000, 1,001~5,000, 5,001~10,000, 10,000+ - **Deployment & Platforms**: 클라우드, SaaS, 웹 기반 - **Supported Languages**: 영어 - **Available Countries**: 미국 ## 특징 - API - Business Intelligence - 대시보드 - 대시보드 만들기 - 데이터 관리 - 데이터 보안 - 데이터 시각화 - 데이터 웨어하우징 - 데이터 캡처 및 전송 - 맞춤형 대시보드 - 보고/분석 - 셀프 서비스 데이터 준비 - 시각 분석 - 정보 거버넌스 - 협업 도구 ## Support Options - 채팅 ## Category - [빅 데이터 소프트웨어](https://www.capterra.co.kr/directory/30851/big-data/software) ## 관련 범주 - [빅 데이터 소프트웨어](https://www.capterra.co.kr/directory/30851/big-data/software) - [데이터 분석 소프트웨어](https://www.capterra.co.kr/directory/31077/data-analysis/software) - [Retail Intelligence](https://www.capterra.co.kr/directory/34633/retail-intelligence/software) - [데이터 관리 소프트웨어](https://www.capterra.co.kr/directory/31003/data-management/software) - [인공 지능 소프트웨어](https://www.capterra.co.kr/directory/30938/artificial-intelligence/software) ## 대안 1. [Google Analytics 360](https://www.capterra.co.kr/software/177042/google-analytics) — 4.7/5 (8091 reviews) 2. [Google Cloud](https://www.capterra.co.kr/software/170983/google-cloud-platform) — 4.7/5 (2282 reviews) 3. [Minitab](https://www.capterra.co.kr/software/109731/minitab-statistical-software) — 4.5/5 (388 reviews) 4. [Sisense](https://www.capterra.co.kr/software/86955/sisense) — 4.5/5 (378 reviews) ## 리뷰 ### "Reliable and Scalable Data Platform That Improves Workflow Efficiency" — 4.0/5 > **Wealth** | *2026년 3월 31일* | 금융 서비스 | Recommendation rating: 8.0/10 > > **장점**: Very strong for handling large datasets and complex queries Makes data processing and transformation much faster compared to traditional tools Flexible for SQL, data engineering, and analytics workflows Integrates well with existing data pipelines and tools we already use > > **단점**: Can get expensive as usage scales Initial setup and environment configuration require some technical effort The interface can feel a bit overwhelming at first, especially for new users > > From my experience, Databricks has been a very solid platform, especially for working with large datasets and building data pipelines. I use it mainly for querying, transforming, and analyzing data, and it has significantly improved performance compared to traditional database tools. It’s particularly useful when dealing with complex data workflows and large volumes of data. That said, there is a bit of a learning curve, and managing costs requires some attention as usage grows. Overall, it’s a reliable and powerful tool that has made data work more efficient and scalable for me. ----- ### "Databricks: Unleashing Data/AI Potential for Next-Level Analytics and Collaboration" — 4.0/5 > **검증된 리뷰어** | *2023년 10월 2일* | 정보 기술 및 서비스 | Recommendation rating: 9.0/10 > > **장점**: unified lakehouse architecture platform with good collaborationmanaged infrastructure with autoscaling \& serverless functionalityautoloader, schema evolution \& delta live tablesunit catalog \& delta sharing for unified governanceMLflow \& integrations with partner connectVersion control databricks repos, secret with security \& complianceReal time processing > > **단점**: Cost \& capacity planning for clusters if you don't use DLT/serverless pipelinesPerformance variabilitySome vendor lock-in if you use "DELTA" format with delta live table > > Very good , able to created end-end lakehouse platform for leading healthcare client ----- ### "Very good to handle very big data" — 3.0/5 > **검증된 리뷰어** | *2020년 9월 29일* | 은행 | Recommendation rating: 8.0/10 > > **장점**: - Enables simultaneous collaborative work with colleagues - Easy to mix spark queries and python for extra analyses and plots - Handful visualization modes for query results (tables and plots with aggregations) > > **단점**: - Hard to manage notebook workspace - Sometimes it gets really slow to run queries - AFAIK, there aren't visualization options for datasets (without running queries) > > While it supports python, when I need to use it, I ultimately prefer to sample or aggregate and export data to work in another environment. For this end, it works very well. ----- ### "A fantastic all-in-one-place platform for big data analytics" — 5.0/5 > **Filippo** | *2023년 9월 21일* | 마케팅 및 광고 | Recommendation rating: 10.0/10 > > **장점**: Databricks can be integrated with the most used cloud services (Amazon, Google, Microsoft) and you can create and manages computation clusters, write code and see results in a single platform instead of having multiple separate services. Its dashboard is really easy to use and allows you to focus on code development. It also supports notebooks versioning with GitLab. > > **단점**: The data visualization part could really be improved. > > We are moving all our big data computation on the Databricks platform. One of the main advantages is the possibility to plan notebooks execution through the workflow section. ----- ### "Powerful tool for dev ops of machine learning models" — 5.0/5 > **Rayla** | *2019년 9월 1일* | 고등 교육 | Recommendation rating: 8.0/10 > > **장점**: I love how easy it is to deploy auto-scaling machine learning models. After a machine learning model is trained, you can just click a button to deploy the model, I believe in a container, and have it auto scale as needed. You can also specify the minimum and maximum size of the deployment to reduce costs but to keep up with the workload as necessary. It is also built around Spark, so tasks involving "big data" aren't an issue. > > **단점**: Some of the cons are that the primary language is Java/Scala, whereas many data scientists are using python or R, which run slower on Databricks than Java and Scala. Also, the main interface via coding, which can limit a lot of citizen data scientists. > > Overall, my experience with Databricks has been very positive. It is a powerful tool to enable data scientists without a lot of data engineering skills. However, you need to be a data scientist or machine learning engineer to be able to take advantage of its power for machine learning. ----- Page: 1 / 2\ 다음: [Next page](https://www.capterra.co.kr/software/148499/databricks?page=2) ## Links - [View on Capterra](https://www.capterra.co.kr/software/148499/databricks) ## This page is available in the following languages | Locale | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | ko | | ----- ## Structured Data