DBMS > Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Vertica vs. YugabyteDB
System Properties Comparison Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Vertica vs. YugabyteDB
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Name | Microsoft Azure Data Explorer Xexclude from comparison | Oracle Xexclude from comparison | Sphinx Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fully managed big data interactive analytics platform | Widely used RDBMS | Open source search engine for searching in data from different sources, e.g. relational databases | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS column oriented | Relational DBMS | Search engine | Relational DBMS Column oriented | 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 Oracle Spatial and Graph RDF store with Oracle Spatial and Graph Spatial DBMS with Oracle Spatial and Graph Vector DBMS since Oracle 23 | Spatial DBMS Time Series DBMS | Document store Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | azure.microsoft.com/services/data-explorer | www.oracle.com/database | sphinxsearch.com | www.vertica.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.microsoft.com/en-us/azure/data-explorer | docs.oracle.com/en/database | sphinxsearch.com/docs | vertica.com/documentation | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | Oracle | Sphinx Technologies Inc. | OpenText previously Micro Focus and Hewlett Packard | Yugabyte Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2019 | 1980 | 2001 | 2005 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | 23c, September 2023 | 3.5.1, February 2023 | 12.0.3, January 2023 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial restricted free version is available | Open Source GPL version 2, commercial licence available | commercial Limited community edition free | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C and C++ | C++ | C++ | C and C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | AIX HP-UX Linux OS X Solaris Windows z/OS | FreeBSD Linux NetBSD OS X Solaris Windows | Linux | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Fixed schema with schema-less datatypes (dynamic) | yes Schemaless in JSON and XML columns | yes | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | no | 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 | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | all fields are automatically indexed | yes | yes full-text index on all search fields | No Indexes Required. Different internal optimization strategy, but same functionality included. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Kusto Query Language (KQL), SQL subset | yes with proprietary extensions | SQL-like query language (SphinxQL) | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC ODBC ODP.NET Oracle Call Interface (OCI) | Proprietary protocol | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C# C++ Clojure Cobol Delphi Eiffel Erlang Fortran Groovy Haskell Java JavaScript Lisp Objective C OCaml Perl PHP Python R Ruby Scala Tcl Visual Basic | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Yes, possible languages: KQL, Python, R | PL/SQL also stored procedures in Java possible | no | yes, PostgreSQL PL/pgSQL, with minor differences | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | no | yes, called Custom Alerts | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding Implicit feature of the cloud service | Sharding, horizontal partitioning | Sharding Partitioning is done manually, search queries against distributed index is supported | horizontal partitioning, hierarchical partitioning | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | Multi-source replication Source-replica replication | none | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Spark connector (open source): github.com/Azure/azure-kusto-spark | no can be realized in PL/SQL | no | no Bi-directional Spark integration | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID isolation level can be parameterized | no | ACID | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes Version 12c introduced the new option 'Oracle Database In-Memory' | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | no | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Microsoft Azure Data Explorer | Oracle | Sphinx | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Cost-based models and subscription-based models are both available. One license is... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Microsoft Azure Data Explorer | Oracle | Sphinx | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | MySQL is the DBMS of the Year 2019 The struggle for the hegemony in Oracle's database empire Architecting eCommerce Platforms for Zero Downtime on Black Friday and Beyond | The DB-Engines ranking includes now search engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Conferences, events and webinars | Oracle Cloud World | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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