DBMS > Brytlyt vs. Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere
System Properties Comparison Brytlyt vs. Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Brytlyt Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Netezza Also called PureData System for Analytics by IBM Xexclude from comparison | PostgreSQL Xexclude from comparison | SAP SQL Anywhere formerly called Adaptive Server Anywhere Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL | Fully managed big data interactive analytics platform | Data warehouse and analytics appliance part of IBM PureSystems | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Website | brytlyt.io | azure.microsoft.com/services/data-explorer | www.ibm.com/products/netezza | www.postgresql.org | www.sap.com/products/technology-platform/sql-anywhere.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.brytlyt.io | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | help.sap.com/docs/SAP_SQL_Anywhere | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Brytlyt | Microsoft | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | SAP formerly Sybase | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 2019 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | 1992 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.0, August 2023 | cloud service with continuous releases | 16.3, May 2024 | 17, July 2015 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | commercial | Open Source BSD | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C, C++ and CUDA | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | hosted | Linux included in appliance | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | AIX HP-UX Linux OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | Fixed schema with schema-less datatypes (dynamic) | yes | 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 | 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 specific XML-type available, but no XML query functionality. | yes | yes specific XML-type available, but no XML query functionality. | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | all fields are automatically indexed | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC native C library ODBC streaming API for large objects | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC ODBC OLE DB | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET HTTP API JDBC ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C++ Delphi Java Perl Python Tcl | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C++ Fortran Java Lua Perl Python R | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Delphi Java JavaScript (Node.js) Perl PHP Python Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions in PL/pgSQL | Yes, possible languages: KQL, Python, R | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes, in C/C++, Java, .Net or Perl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding Implicit feature of the cloud service | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | none | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Source-replica replication Database mirroring | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | Users with fine-grained authorization concept | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3rd parties | Redgate webinars: A series of key topics for new PostgreSQL users.
» more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more pgDash: In-Depth PostgreSQL Monitoring. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today! » more CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more Instaclustr: Fully Hosted & Managed PostgreSQL » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Brytlyt | Microsoft Azure Data Explorer | Netezza Also called PureData System for Analytics by IBM | PostgreSQL | SAP SQL Anywhere formerly called Adaptive Server Anywhere | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform London data analytics startup Brytlyt raises €4.43M from Amsterdam-based Finch Capital, others Brytlyt becomes NVIDIA Inception Premier Partner Bringing GPUs To Bear On Bog Standard Relational Databases Brytlyt raises £3.8m for '1000x faster analytics' provided by Google News | We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Azure Data Explorer: Log and telemetry analytics benchmark Controlling costs in Azure Data Explorer using down-sampling and aggregation Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services provided by Google News | Roundup: Telehouse, Cloudera, Netezza, EMC IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS AWS and IBM Netezza come out in support of Iceberg in table format face-off Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services IBM Brings Back a Netezza, Attacks Yellowbrick provided by Google News | What Microsoft's Open Source PostgreSQL Acquisition Portends for SQL Server How to implement a better like, views, comment counters in PostgreSQL? Automatically Generate Types for Your PostgreSQL Database Enterprise DB begins rolling AI features into PostgreSQL Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need provided by Google News | SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now! SAP Again Named a Leader in 2021 Gartner® Magic Quadrant™ for Cloud Database Management Systems Securing SAP with AWS Network Firewall: Part 2 – Managed Rules | Amazon Web Services MindsDB is now the leading and fastest growing applied ML platform in the world India - English Gartner’s Magic Quadrant for Cloud Database Management Systems provided by Google News |
Share this page