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Google Spanner Unifies OLTP and OLAP with Columnar Engine
Google Spanner now features a columnar engine, allowing its distributed database to handle both OLTP and OLAP workloads on a single platform. This hybrid architecture eliminates the need for separate data warehouses and ETL pipelines. The engine's columnar storage and vectorized execution accelerate analytical queries up to 200x on live data, which is especially beneficial for AI applications.
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Distributed Multi-Modal Database Aerospike 8 Brings Support for Real-Time ACID Transactions
Aerospike has announced version 8.0 of its distributed multi-modal database, bringing support for distributed ACID transactions. This enables large-scale online transaction processing (OLTP) applications like banking, e-commerce, inventory management, health care, order processing, and more, says the company.
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Grab Shared Its Experience in Designing Distributed Data Platform
GrabApp is an application that customers select and buy their daily needs from merchants. To be scalable and manageable the data platform and ingestion should be designed as a distributed, fault-tolerant. To design this data platform two classes of data stores are considered: OLTP and OLAP.
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Improving Azure SQL Database Performance Using In-Memory Technologies
In late 2016, Microsoft announced the general availability of Azure SQL Database In-Memory technologies. In-Memory processing is only available in Azure Premium database tiers and provides performance improvements for On-line Analytical Processing (OLTP), Clustered Columnstore Indexes and Non-clustered Columnstore Indexes for Hybrid Transactional and Analytical Processing (HTAP) scenarios.
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Column-based Storage in SQL Server 2011
Imagine ad hock data mining queries against a single table with 1 TB of data and 1.44 billion rows coming back in roughly a second. This is the scenario Microsoft intends to support using 32-core machines and their new column-based storage engine.