DBMS > CouchDB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere vs. Solr
System Properties Comparison CouchDB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere vs. Solr
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Name | CouchDB stands for "Cluster Of Unreliable Commodity Hardware" Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | SAP SQL Anywhere formerly called Adaptive Server Anywhere Xexclude from comparison | Solr Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones. | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Fully managed big data interactive analytics platform | RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments | A widely used distributed, scalable search engine based on Apache Lucene | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Key-value store Wide column store | Relational DBMS column oriented | Relational DBMS | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS using the Geocouch extension | 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 | Spatial DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | couchdb.apache.org | cloud.google.com/bigtable | azure.microsoft.com/services/data-explorer | www.sap.com/products/technology-platform/sql-anywhere.html | solr.apache.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.couchdb.org/en/stable | cloud.google.com/bigtable/docs | docs.microsoft.com/en-us/azure/data-explorer | help.sap.com/docs/SAP_SQL_Anywhere | solr.apache.org/resources.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer | Microsoft | SAP formerly Sybase | Apache Software Foundation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2005 | 2015 | 2019 | 1992 | 2006 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 3.3.3, December 2023 | cloud service with continuous releases | 17, July 2015 | 9.6.1, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache version 2 | commercial | commercial | commercial | Open Source Apache Version 2 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Erlang | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Android BSD Linux OS X Solaris Windows | hosted | hosted | AIX HP-UX Linux OS X Solaris Windows | All OS with a Java VM runs as a servlet in servlet container (e.g. Tomcat, Jetty is included) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | Fixed schema with schema-less datatypes (dynamic) | yes | yes Dynamic Fields enables on-the-fly addition of new fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | no | no | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | yes supports customizable data types and automatic typing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | no | no | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes via views | no | all fields are automatically indexed | yes | yes All search fields are automatically indexed | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | no | Kusto Query Language (KQL), SQL subset | yes | Solr Parallel SQL Interface | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP/JSON API | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET HTTP API JDBC ODBC | Java API RESTful HTTP/JSON API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# ColdFusion Erlang Haskell Java JavaScript Lisp Lua Objective-C OCaml Perl PHP PL/SQL Python Ruby Smalltalk | C# C++ Go Java JavaScript (Node.js) Python | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C# C++ Delphi Java JavaScript (Node.js) Perl PHP Python Ruby | .Net Erlang Java JavaScript any language that supports sockets and either XML or JSON Perl PHP Python Ruby Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | View functions in JavaScript | no | Yes, possible languages: KQL, Python, R | yes, in C/C++, Java, .Net or Perl | Java plugins | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | yes User configurable commands triggered on index changes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding improved architecture with release 2.0 | Sharding | Sharding Implicit feature of the cloud service | none | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication Source-replica replication | Internal replication in Colossus, and regional replication between two clusters in different zones | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication Database mirroring | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Eventual Consistency Immediate Consistency | Immediate Consistency | Eventual Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no atomic operations within a single document possible | Atomic single-row operations | no | ACID | optimistic locking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes strategy: optimistic locking | 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 | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per database | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CouchDB stands for "Cluster Of Unreliable Commodity Hardware" | Google Cloud Bigtable | Microsoft Azure Data Explorer | SAP SQL Anywhere formerly called Adaptive Server Anywhere | Solr | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | Elasticsearch replaced Solr as the most popular search engine Enterprise Search Engines almost double their popularity in the last 12 months The DB-Engines ranking includes now search engines How to Automate A Blog Post App Deployment With GitHub Actions, Node.js, CouchDB, and Aptible How to install the CouchDB NoSQL database on Debian Server 11 IBM Cloudant pulls plan to fund new foundational layer for CouchDB CouchDB 3.0 ends admin party era • DEVCLASS Tracking Expenses with CouchDB and Angular — SitePoint provided by Google News Google's AI-First Strategy Brings Vector Support To Cloud Databases Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Review: Google Bigtable scales with ease Google Cloud makes it cheaper to run smaller workloads on Bigtable provided by Google News We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates provided by Google News SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now! SAP Products & Services Data Portfolio 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 SAP launches HANA cloud platform, partners with Siemens, Intel provided by Google News SOLR-led walkout demands better conditions for Compass workers Solr Network Launches Groundbreaking Solana Token Creator (SOLR) Proactive Strategies Have Insiders Been Buying Solar Alliance Energy Inc. (CVE:SOLR) Shares? SOLR hosts teach-in of labor movements at Northwestern provided by Google News |
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