DBMS > Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. MongoDB vs. Vertica
System Properties Comparison Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. MongoDB vs. Vertica
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Name | Hazelcast Xexclude from comparison | Ingres Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | MongoDB Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A widely adopted in-memory data grid | Well established RDBMS | 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 | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store | Relational DBMS | Relational DBMS column oriented | Document store | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store JSON support with IMDG 3.12 | 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 | Spatial DBMS Time Series DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | hazelcast.com | www.actian.com/databases/ingres | azure.microsoft.com/services/data-explorer | www.mongodb.com | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | hazelcast.org/imdg/docs | docs.actian.com/ingres | docs.microsoft.com/en-us/azure/data-explorer | www.mongodb.com/docs/manual | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Hazelcast | Actian Corporation | Microsoft | MongoDB, Inc | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 1974 originally developed at University Berkely in early 1970s | 2019 | 2009 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.3.6, November 2023 | 11.2, May 2022 | cloud service with continuous releases | 6.0.7, June 2023 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; commercial licenses available | commercial | 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. | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no MongoDB available as DBaaS (MongoDB Atlas) | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | C | C++ | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM | AIX HP Open VMS HP-UX Linux Solaris Windows | hosted | Linux OS X Solaris Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | 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, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 the object must implement a serialization strategy | no but tools for importing/exporting data from/to XML-files available | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | all fields are automatically indexed | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | yes | Kusto Query Language (KQL), SQL subset | Read-only SQL queries via the MongoDB Atlas SQL Interface | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JCache JPA Memcached protocol RESTful HTTP API | .NET Client API JDBC ODBC proprietary protocol (OpenAPI) | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C# C++ Clojure Go Java JavaScript (Node.js) Python 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 | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes Event Listeners, Executor Services | yes | Yes, possible languages: KQL, Python, R | JavaScript | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes Events | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes in MongoDB Atlas only | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | horizontal partitioning Ingres Star to access multiple databases simultaneously | 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. | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes Replicated Map | Ingres Replicator | 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 | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency selectable by user Raft Consensus Algorithm | Immediate Consistency | Eventual Consistency Immediate Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | no typically not used, however similar functionality with DBRef possible | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | one or two-phase-commit; repeatable reads; read commited | ACID | no | Multi-document ACID Transactions with snapshot isolation | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes MVCC | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes optional, enabled by default | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | no | yes In-memory storage engine introduced with MongoDB version 3.2 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Role-based access control | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | Access rights for users and roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Hazelcast | Ingres | Microsoft Azure Data Explorer | MongoDB | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Built around the flexible document data model and unified API, MongoDB is a developer... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | Cost-based models and subscription-based models are both available. One license is... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Hazelcast | Ingres | Microsoft Azure Data Explorer | MongoDB | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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