DBMS > Apache Pinot vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. PostgreSQL
System Properties Comparison Apache Pinot vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. PostgreSQL
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Name | Apache Pinot Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Microsoft SQL Server Xexclude from comparison | PostgreSQL Xexclude from comparison | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency | Fully managed big data interactive analytics platform | Microsofts flagship relational DBMS | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Relational DBMS column oriented | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Graph DBMS Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | pinot.apache.org | azure.microsoft.com/services/data-explorer | www.microsoft.com/en-us/sql-server | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.pinot.apache.org | docs.microsoft.com/en-us/azure/data-explorer | learn.microsoft.com/en-US/sql/sql-server | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation and contributors | Microsoft | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2019 | 1989 | 1989 1989: Postgres, 1996: PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.0.0, September 2023 | cloud service with continuous releases | SQL Server 2022, November 2022 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2.0 | commercial | commercial restricted free version is available | Open Source BSD | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java JDK11 or higher | hosted | Linux Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | Fixed schema with schema-less datatypes (dynamic) | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | yes | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC ODBC OLE DB Tabular Data Stream (TDS) | ADO.NET JDBC native C library ODBC streaming API for large objects | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Go Java Python | .Net Go Java JavaScript (Node.js) PowerShell Python R | C# C++ Delphi Go Java JavaScript (Node.js) PHP Python R Ruby Visual Basic | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Yes, possible languages: KQL, Python, R | Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | Sharding Implicit feature of the cloud service | tables can be distributed across several files (horizontal partitioning); sharding through federation | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | yes, but depending on the SQL-Server Edition | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache Pinot | Microsoft Azure Data Explorer | Microsoft SQL Server | PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | MySQL is the DBMS of the Year 2019 The struggle for the hegemony in Oracle's database empire Microsoft SQL Server is the DBMS of the Year | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Monitoring PostgreSQL with Redgate Monitor StarTree Finds Apache Pinot the Right Vintage for IT Observability StarTree Makes Observability Case for Apache Pinot Database StarTree broadly enhances Apache Pinot-based analytics platform Open source Apache Pinot advances as StarTree boosts real-time analytics and observability Real-Time Analytics for Mobile App Crashes using Apache Pinot provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services provided by Google News SQL Server vNext: When and What Is Coming Configure change data capture parameters on Amazon RDS for SQL Server | Amazon Web Services Microsoft Ships Data API Builder for Azure SQL Databases SQL Server 2014 end of support: Keep your customers secure How to Know When It's Time for a Microsoft SQL Server Upgrade provided by Google News Distributed PostgreSQL Buyers Guide Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... SolarWinds Unveils Enhanced Database Performance Analyzer with Advanced PostgreSQL Support ServiceNow trades MariaDB for RaptorDB (PostgreSQL) anynines Launches Quick & Easy PostgreSQL Management in Local Kubernetes Clusters with a9s CLI provided by Google News |
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