In an increasingly competitive digital economy, businesses depend on applications more than ever.
Modern business and consumer applications operating across native, web, and mobile platforms
rely on fast access to data. To meet business requirements for reliability and availability, databases
that support these applications must deliver high performance and increased stability on a security-
focused foundation. Development and operations teams need databases and their underlying operating systems to provide modern development languages, tools, and technologies that support rapid
development and innovation. Additionally, IT teams must standardize on a consistent, cross-infrastructure foundation that simplifies IT operations and offers database and application portability.

Together, Red Hat and Microsoft deliver a highly available and reliable foundation for database operations that meets modern digital business needs.


Microsoft continues to adopt open source solutions, including Red Hat® Enterprise Linux ®. Microsoft SQL Server 2017 on Linux is a database management system for critical workloads
ranging from small, single-machine applications to large, enterprise-scale, and internet-facing
applications with thousands of concurrent users. It supports a variety of development languages
and performance features in on-premise, hybrid, container, and cloud installations. Red Hat
Enterprise Linux, an enterprise open source operating system, provides a consistent foundation
for bare-metal, virtualized, container, and public and private cloud infrastructures. Built-in security
and management capabilities provide a stable, high-performance platform for critical workloads.
SQL Server 2017 on Linux delivers key features of the relational database engine — including in-memory performance for operational and data warehousing workloads, increased data security, Microsoft
Active Directory authentication, high availability, disaster recovery, and SQL Server Agent — to the
Red Hat Enterprise Linux ecosystem. Red Hat’s platform increases security, stability, reliability, and
manageability for SQL Server across deployment environments. As the reference platform for SQL
Server 2017 on Linux, all development, co-engineering, and quality testing was first performed on
Red Hat Enterprise Linux.


Red Hat Enterprise
Linux is trusted by 90%
of the Fortune 500.

Microsoft SQL Server 2017 on Linux is not a port or rewrite. It is the same efficient, scalable relational
database management system (RDBMS) that Microsoft has delivered for years, available with equal
functionality, performance, and scalability on Red Hat Enterprise Linux. The SQL Server Platform
Abstraction Layer (SQLPAL) abstracts operating system and library calls and semantics to optimize
SQL Server 2017 for each platform (Figure 1). All operating system-specific code is contained in a
single location, keeping all other SQL Server code platform-agnostic. To accomplish this abstraction, SQLPAL combines portions of the Microsoft Research Drawbridge project with SQL Server
Operating System, the existing SQL Server platform layer. SQLPAL abstracts the underlying operating
system from applications, while the host extension — natively compiled for Linux — provides robust
memory management, thread scheduling, and input-output (I/O) services. As a result, the SQL Server
Database Engine — the core service for storing, processing, and securing data — is fully supported
with optimized performance and capabilities on Red Hat Enterprise Linux. Microsoft also maintains
package repositories for installing SQL Server on Red Hat Enterprise Linux and supports installation
via the native YUM package manager.


Red Hat Enterprise Linux is the most- deployed operating system in public cloud environments

All Microsoft SQL Server 2017 editions — Enterprise, Standard, Developer, Web, and Express — run
on Red Hat Enterprise Linux, letting you choose the edition that best fits your technical and business
needs. Use built-in images from the Microsoft Azure Marketplace to deploy Red Hat Enterprise Linux
and SQL Server on Azure virtual machines (VMs) that are certified for Red Hat Enterprise Linux and
meet SQL Server’s minimum technical requirements.
SQL Server supports a variety of network- and direct-attached storage technologies and protocols — including Fibre Channel Storage Attached Network (FC SAN), Fibre Channel over Ethernet
(FCoE), Internet Small Computer Systems Interface (iSCSI), Network File System (NFS), and
Samba — so you can choose the storage that best fits your organization’s needs. Petabyte-scale data
warehousing with in-memory clustered columnstore indexes store massive amounts of data that can be
modified and loaded concurrently for data warehouse and decision support system (DSS) workloads.
For large, critical applications, SQL Server Enterprise Edition on Red Hat Enterprise Linux combines
enterprise-grade features with massive scalability on an unlimited number of cores. Each SQL Server
instance can use as much memory as Red Hat Enterprise Linux can allocate, with a maximum database size of 524PB.


Red Hat Enterprise Linux is Common Criteria and Federal Information Processing Standards (FIPS) 140-2 certified—and is the first operating system with Linux Container Framework support to be Common Criteria- certified (v7.1).

Security is at the core of SQL Server on Red Hat Enterprise Linux. Red Hat provides advanced security technologies with ongoing support from its product security team to combat threats and protect your data. SQL Server includes a robust set of features — such as auditing, Row-Level Security,
dynamic data masking, Always Encrypted, and Transparent Data Encryption — that separate and
protect organizational data at rest and in motion.
Additionally, Red Hat Enterprise Linux integrates with Active Directory, allowing it to function as the hub for user identity management. Two integration options are available: direct integration and Active
Directory cross-realm trust (Figure 2). With direct integration, Red Hat Enterprise Linux systems are joined directly into an Active Directory domain. In an Active Directory cross-realm trust, cross-forest Kerberos trusts with Active Directory let external Active Directory users access resources in the Red Hat Identity Management domain.


Microsoft SQL Server has had the fewest vulnerabilities over the past 7 years compared to all other major database vendors.

Red Hat Enterprise Linux and SQL Server support open source and cross-platform tooling, as well as all existing driver and development frameworks, so you can manage your SQL Server database using
your current tools, methodologies, and processes. Present Microsoft Windows-based tools, including
SQL Server Management Studio (SSMS) and SQL Server Data Tools (SSDT), continue to work with Red Hat Enterprise Linux. SQL Server supports new tools, like SQL Operations Studio, Visual Studio (VS) Code Extension for SQL Server, and mssql-cli, across all platforms. Plus, Red Hat and Microsoft work together and with other tool vendors to support many industry-leading third-party tools.


Microsoft SQL Server on Red Hat Enterprise Linux offers instance- and database-level high availability (HA) through integration with Pacemaker, a high availability cluster resource manager optimized
for Red Hat Enterprise Linux. With orchestration capabilities for monitoring, failure detection, and automatic failover, Pacemaker detects and recovers applications and VMs in the event of node- or
resource-level failures. Red Hat provides detailed Pacemaker configuration information to optimize operations, while SQL Server uses unique Pacemaker-specific resource agents to implement instance-
and database-level HA. Microsoft also maintains a separate package repository for open source,
Pacemaker-specific agents for SQL Server.
Additionally, SQL Server supports instance-level HA and redundancy with Always On Failover Cluster
Instances (FCI) to ensure SQL Server instances remain available during planned and unplanned
outages. An FCI comprises two or more cluster nodes with access to storage area network (SAN)
or direct-attached cluster shared storage. Only one node is active at any time. Secondary nodes
are passive but ready to assume the role of active node during failover. Pacemaker manages all FCI
cluster resources running on Red Hat Enterprise Linux.
SQL Server achieves database-level HA and disaster recovery with Always On Availability Groups.
These groups support a replicated environment for a discrete set of user databases, known as availability databases, running on similarly configured hardware. Several types of non-exclusive availability
groups are possible with SQL Server and Red Hat Enterprise Linux:
Availability groups configured for high availability and disaster recovery are sets of databases that fail over together. They provide high availability, disaster recovery, and read-scale balancing using Pacemaker as the cluster manager.
Availability groups configured for read-only, scale-out workloads are sets of databases that are replicated to other instances of SQL Server for applicable workloads. They do not require a
cluster manager.
Distributed availability groups span two separate availability groups for failover and disaster recovery purposes. Underlying availability groups can be configured on the same platform and managed
by Pacemaker — or placed on different platforms for migration and disaster recovery purposes.
Cross-platform availability groups include one or more replicas on both Microsoft Windows and
Red Hat Enterprise Linux, providing multiplatform support and minimizing application disruption for
database migrations between Windows and Linux.
Each availability group can have one primary replica and up to eight secondary replicas. Other capabilities include multidatabase failover, multiple synchronous and asynchronous secondaries, manual or
automatic failover, and active secondaries for read and backup workloads.


Together, Red Hat Enterprise Linux and Microsoft SQL Server 2017 Enterprise Edition deliver leading performance for your database workloads. The Transaction Processing Performance Council
Benchmark H (TPC-H) measures decision support system price per performance. In the first TPC-H result with Microsoft SQL Server 2017 Enterprise Edition, the combination of SQL Server 2017 and Red Hat Enterprise Linux 7.3 surpassed the previous leading TPC-H@1000GB nonclustered result,
achieved with SQL Server 2016, by 6%. This combination also displayed 5% lower price per performance maintenance costs over three years


As the foundation for SQL Server deployments, Red Hat Enterprise Linux accelerates database workloads with built-in performance features that require little or no configuration.
Direct I/O
A Red Hat Enterprise Linux file system feature, direct I/O helps applications like SQL Server effectively manage high file I/O throughput. Applications bypass operating system caches and directly read and
write files to storage devices. SQL Server automatically configures direct I/O to increase database
workload performance with no requirement for user interaction.
Non-uniform memory access (NUMA) awareness
In modern, multiprocessor systems, memory access times are dependent on the relative locations of memory and CPUs. Access to memory that is local to a particular CPU is faster than memory connected to a remote CPU. As a result, these servers typically support NUMA, an approach that divides
system memory into zones and allocates each zone to a particular processor. SQL Server detects the
presence of NUMA systems and takes advantage of the process affinity feature in Red Hat Enterprise
Linux. When configured, process affinity runs processes on specific CPUs, ensuring that each
process uses local memory. This method speeds memory access and increases overall database
workload performance.
Transparent huge pages (THP)
Huge pages reduce the overhead for managing large amounts of memory by increasing the size of
memory pages to 2MB and 1GB. THP is an abstraction layer that automates most aspects of creating,
managing, and using huge pages. With testing and optimization across a range of systems, configurations, applications, and workloads, its default settings improve the performance of most system configurations. Red Hat Enterprise Linux supports THP to increase memory utilization and performance
for Microsoft SQL Server.


Microsoft SQL Server columnstore indexes can boost analytic and data warehousing workload performance by up to 100x and data compression by up to 10x

Red Hat is the world’s leading
provider of open source software
solutions, using a community-
powered approach to provide
reliable and high-performing
cloud, Linux, middleware,
storage, and virtualization
technologies. Red Hat also
offers award-winning support,
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As a connective hub in a global
network of enterprises, partners,
and open source communities,
Red Hat helps create relevant,
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and prepare customers for the
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Microsoft SQL Server accelerates database workloads using advanced performance features.
Capabilities like dynamic memory object scaling, parallel redo recovery, and read ahead are built into
SQL Server and do not require user intervention. Other features — including in-memory online transactional processing (OLTP), hybrid transactional/analytical processing (HTAP), and adaptive query
processing and automatic tuning — require user configuration. SQL Server provides its own memory
management capabilities for buffer pool and query plan caches.
Columnstore indexes
With columnstore indexes, a key SQL Server performance feature, analytics and data warehousing
workloads can achieve up to 100 times better performance. Data compression is based on columns
instead of rows for up to tenfold better data compression. Column and rowgroup elimination permits
the database to skip columns and rows that are not needed. Batch mode execution processes rows in
groups, accelerating operations.
In-memory online transactional processing (OLTP)
In-memory OLTP increases transaction processing performance. It removes lock and latch contention
between concurrently executing transactions. Optimized data storage, access, and processing algorithms use enhancements in in-memory and high concurrency computing to improve data access and
transaction execution efficiency. SQL Server’s in-memory OLTP features include memory-optimized
tables and table variables, as well as natively compiled stored procedures and scalar user-defined
functions (UDFs).
Hybrid transactional/analytical processing (HTAP)
Combining in-memory OLTP with real-time analytics capabilities, HTAP processes high-performance
transactional and analytical workloads on a single platform. Using HTAP, SQL Server manages
two copies of data: one for in-memory OLTP workloads and one for real-time analytic workloads.
Employing nonclustered columnstore indexes, SQL Server automatically and instantly reflects data
changes made by OLTP workloads within analytical workload data, reducing latency and providing
real-time operational analytics capabilities.
Adaptive query processing and automatic tuning
SQL Server uses adaptive query processing and automatic tuning to further increase database performance and address performance degradations. With adaptive query processing, SQL Server adapts
to customer workloads by optimizing its query plan based on the performance of the previous query.
Automatic tuning maintains data query performance by detecting and automatically correcting performance issues using the rich telemetry of Query Store.
Modern businesses depend on their applications. Together, Red Hat Enterprise Linux and Microsoft
SQL Server 2017 deliver data reliability and availability for critical workloads. Dynamic scalability
ensures applications can access the data and resources they need, while advanced security features
help protect your data at rest and in motion. Instance- and database-level HA increase database stability, and a variety of performance capabilities and features accelerate database operations. Support
for open source and cross-platform tooling lets you manage your SQL Server database using your
current tools, methods, and processes.
Contact your Red Hat or Microsoft sales representative to find out how to build a reliable, high-performance, and security-focused database foundation for your applications.