DBMS > BaseX vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Teradata Aster vs. TimesTen
System Properties Comparison BaseX vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Teradata Aster vs. TimesTen
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Name | BaseX Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | PostgreSQL Xexclude from comparison | Teradata Aster Xexclude from comparison | TimesTen Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI. | Fully managed big data interactive analytics platform | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Platform for big data analytics on multistructured data sources and types | In-Memory RDBMS compatible to Oracle | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Native XML DBMS | Relational DBMS column oriented | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | basex.org | azure.microsoft.com/services/data-explorer | www.postgresql.org | www.oracle.com/database/technologies/related/timesten.html | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.basex.org | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | docs.oracle.com/database/timesten-18.1 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | BaseX GmbH | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | Teradata | Oracle, TimesTen Performance Software, HP originally founded in HP Labs it was acquired by Oracle in 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2007 | 2019 | 1989 1989: Postgres, 1996: PostgreSQL | 2005 | 1998 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 10.7, August 2023 | cloud service with continuous releases | 16.2, February 2024 | 11 Release 2 (11.2.2.8.0) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source BSD license | commercial | Open Source BSD | commercial | 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. | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux | AIX HP-UX Linux OS X Solaris SPARC/x86 Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | Fixed schema with schema-less datatypes (dynamic) | yes | Flexible Schema (defined schema, partial schema, schema free) defined schema within the relational store; partial schema or schema free in the Aster File Store | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | no XQuery supports types | 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 | yes specific XML-type available, but no XML query functionality. | yes in Aster File Store | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | all fields are automatically indexed | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | Kusto Query Language (KQL), SQL subset | yes standard with numerous extensions | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Java API RESTful HTTP API RESTXQ WebDAV XML:DB XQJ | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC ODBC OLE DB | JDBC ODBC ODP.NET Oracle Call Interface (OCI) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Actionscript C C# Haskell Java JavaScript Node.js Lisp Perl PHP Python Qt Rebol Ruby Scala Visual Basic | .Net Go Java JavaScript (Node.js) PowerShell Python R | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Java Python R | C C++ Java PL/SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | Yes, possible languages: KQL, Python, R | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | R packages | PL/SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes via events | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding Implicit feature of the cloud service | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | none | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication other methods possible by using 3rd party extensions | yes Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured. | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | yes SQL Map-Reduce Framework | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency or Eventual Consistency depending on configuration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | multiple readers, single writer | 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 by means of logfiles and checkpoints | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Users with fine-grained authorization concept on 4 levels | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
BaseX | Microsoft Azure Data Explorer | PostgreSQL | Teradata Aster | TimesTen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Conferences, events and webinars | Monitoring PostgreSQL with Redgate Monitor | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | XML Injection Attacks: What to Know About XPath, XQuery, XXE & More 9 Skills You Need to Become a Data Engineer 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 General availability: New KQL function to enrich your data analysis with geographic context | Azure updates Azure Data Explorer and Stream Analytics for anomaly detection Controlling costs in Azure Data Explorer using down-sampling and aggregation provided by Google News | Automatically Generate Types for Your PostgreSQL Database Baffle Delivers Enterprise-Grade Data Security for PostgreSQL on Amazon RDS and Amazon Aurora Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Your MySQL 5.7 and PostgreSQL 11 databases will be automatically enrolled into Amazon RDS Extended Support ... Why PostgreSQL Is the Bedrock for the Future of Data provided by Google News | Mellanox InfiniBand Helps Accelerate Teradata Aster Big Analytics Appliance Teradata Aster Analytics Going Places: On Hadoop and AWS Northwestern Analytics Partners with Teradata Aster to Host Hackathon Teradata's Aster shows how the flowers of fraud bloom Case study: Siemens reduces train failures with Teradata Aster provided by Google News | In-memory databases with Emulex Gen 7 provided by Google News |
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