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Azure Data Lake Store: A Hyperscale Distributed File Service for Big Data Analytics
Summary: ADLS is a fully-managed, exabyte-scale file service optimized for parallel big-data analytics, unifying HDFS compatibility with Cosmos semantics and co-located compute/data. It bridges Cosmos and Hadoop with an HDFS-compatible API, adds multi-tier storage and security, and outlines Cosmos-to-ADLS migration.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5349
- Venue
- SIGMOD
- Year
- 2017
- Pagerank
- 7.6624689e-05
- Overall Rank
- 3,044 | 78.85%
- DOI
-
10.1145/3035918.3056100
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 23 of 23 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 1,921 |
Selecting Subexpressions to Materialize at Datacenter Scale |
2018 |
VLDB |
0.00010085899 |
| 2,060 |
Dremel: A Decade of Interactive SQL Analysis at Web Scale |
2020 |
VLDB |
9.6585115e-05 |
| 2,080 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
9.5954034e-05 |
| 2,366 |
Data Market Platforms: Trading Data Assets to Solve Data Problems |
2020 |
VLDB |
8.9521259e-05 |
| 2,542 |
POLARIS: The Distributed SQL Engine in Azure Synapse |
2020 |
VLDB |
8.5681631e-05 |
| 2,955 |
Magpie: Python at Speed and Scale using Cloud Backends |
2021 |
CIDR |
7.8188583e-05 |
| 3,409 |
End-to-end Optimization of Machine Learning Prediction Queries |
2022 |
SIGMOD |
7.1240791e-05 |
| 3,623 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9017341e-05 |
| 5,501 |
To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams |
2021 |
SIGMOD |
5.4731481e-05 |
| 5,571 |
A Deep Dive into Common Open Formats for Analytical DBMSs |
2023 |
VLDB |
5.4279553e-05 |
| 6,241 |
Helios: Hyperscale Indexing for the Cloud & Edge |
2020 |
VLDB |
5.1357476e-05 |
| 6,278 |
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward |
2021 |
VLDB |
5.1241654e-05 |
| 6,671 |
Incorporating Super-Operators in Big-Data Query Optimizers |
2020 |
VLDB |
4.9625353e-05 |
| 7,099 |
KEA: Tuning an Exabyte-Scale Data Infrastructure |
2021 |
SIGMOD |
4.8263529e-05 |
| 7,778 |
Runtime Variation in Big Data Analytics |
2023 |
SIGMOD |
4.6491879e-05 |
| 8,517 |
Extending Polaris to Support Transactions |
2024 |
SIGMOD |
4.4897788e-05 |
| 8,754 |
Hyperspace: The Indexing Subsystem of Azure Synapse |
2021 |
VLDB |
4.4520434e-05 |
| 8,781 |
Bringing Cloud-Native Storage to SAP IQ |
2021 |
SIGMOD |
4.4479873e-05 |
| 9,138 |
Phoebe: A Learning-based Checkpoint Optimizer |
2021 |
VLDB |
4.3842765e-05 |
| 9,236 |
AutoComp: Automated Data Compaction for Log-Structured Tables in Data Lakes |
2025 |
SIGMOD |
4.3648789e-05 |
| 9,700 |
Towards Functional Decomposition of Storage Formats |
2025 |
CIDR |
4.2967256e-05 |
| 10,808 |
GraphAr: An Efficient Storage Scheme for Graph Data in Data Lakes |
2025 |
VLDB |
4.1905499e-05 |
| 11,219 |
Efficient Approximation Framework for Attribute Recommendation |
2023 |
SIGMOD |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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