DBMS > Ignite vs. Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL vs. SingleStore
System Properties Comparison Ignite vs. Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL vs. SingleStore
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Name | Ignite Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | MongoDB Xexclude from comparison | PostgreSQL Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale. | Fully managed big data interactive analytics platform | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store Relational DBMS | Relational DBMS column oriented | Document store | 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 | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | ignite.apache.org | azure.microsoft.com/services/data-explorer | www.mongodb.com | www.postgresql.org | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | apacheignite.readme.io/docs | docs.microsoft.com/en-us/azure/data-explorer | www.mongodb.com/docs/manual | www.postgresql.org/docs | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation | Microsoft | MongoDB, Inc | PostgreSQL Global Development Group www.postgresql.org/developer | SingleStore Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2019 | 2009 | 1989 1989: Postgres, 1996: PostgreSQL | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | Apache Ignite 2.6 | cloud service with continuous releases | 6.0.7, June 2023 | 16.3, May 2024 | 8.5, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache 2.0 | commercial | Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. | Open Source BSD | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no MongoDB available as DBaaS (MongoDB Atlas) | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++, Java, .Net | C++ | C | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Solaris Windows | hosted | Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | Fixed schema with schema-less datatypes (dynamic) | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. | 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 string, integer, double, decimal, boolean, date, object_id, geospatial | 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. | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | all fields are automatically indexed | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | ANSI-99 for query and DML statements, subset of DDL | Kusto Query Language (KQL), SQL subset | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes standard with numerous extensions | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | ADO.NET JDBC native C library ODBC streaming API for large objects | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Java PHP Python Ruby Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes (compute grid and cache interceptors can be used instead) | Yes, possible languages: KQL, Python, R | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes (cache interceptors and events) | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes in MongoDB Atlas only | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding Implicit feature of the cloud service | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes (replicated cache) | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Source-replica replication stores two copies of each physical data partition on two separate nodes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes (compute grid and hadoop accelerator) | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no typically not used, however similar functionality with DBRef possible | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | Multi-document ACID Transactions with snapshot isolation | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes optional, enabled by default | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes In-memory storage engine introduced with MongoDB version 3.2 | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Security Hooks for custom implementations | Azure Active Directory Authentication | Access rights for users and roles | fine grained access rights according to SQL-standard | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Ignite | Microsoft Azure Data Explorer | MongoDB | PostgreSQL | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Built around the flexible document data model and unified API, MongoDB is a developer... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | Customers in various industries worldwide including US and International Industry... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | F ree Tier and Enterprise Edition » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Ignite | Microsoft Azure Data Explorer | MongoDB | PostgreSQL | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Snowflake is the DBMS of the Year 2021 PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 | 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 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 Apache Ignite: An Overview GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ... What is Apache Ignite? How is Apache Ignite Used? Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services provided by Google News Update records in a Kusto Database (public preview) | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates Public Preview: Azure Data Explorer Add-On for Splunk | Azure updates Azure Data Explorer: Log and telemetry analytics benchmark provided by Google News Should You Buy MongoDB, Snowflake, and Atlassian at Their 52-Week Lows? Why MongoDB Plunged Over 35% in May CE 100 Index Slips 1.1% as MongoDB Shares Slide After Earnings Looking Into MongoDB's Recent Short Interest - MongoDB (NASDAQ:MDB) This Analyst With 85% Accuracy Rate Sees Over 29% Upside In MongoDB - Here Are 5 Stock Picks For Last Wee provided by Google News Raise the bar on AI-powered app development with Azure Database for PostgreSQL How to implement a better like, views, comment counters in PostgreSQL? Automatically Generate Types for Your PostgreSQL Database First Principles: Optimizing PostgreSQL for the cloud Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... provided by Google News Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore update adds new tools to fuel GenAI, analytics SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files provided by Google News |
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