DBMS > Elasticsearch vs. Ignite vs. Microsoft Azure Data Explorer vs. Snowflake vs. Tarantool
System Properties Comparison Elasticsearch vs. Ignite vs. Microsoft Azure Data Explorer vs. Snowflake vs. Tarantool
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Name | Elasticsearch Xexclude from comparison | Ignite Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Snowflake Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric | 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 | Cloud-based data warehousing service for structured and semi-structured data | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Search engine | Key-value store Relational DBMS | Relational DBMS column oriented | Relational DBMS | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Spatial DBMS Vector DBMS | 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 with Tarantool/GIS extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.elastic.co/elasticsearch | ignite.apache.org | azure.microsoft.com/services/data-explorer | www.snowflake.com | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.elastic.co/guide/en/elasticsearch/reference/current/index.html | apacheignite.readme.io/docs | docs.microsoft.com/en-us/azure/data-explorer | docs.snowflake.net/manuals/index.html | www.tarantool.io/en/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Elastic | Apache Software Foundation | Microsoft | Snowflake Computing Inc. | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2010 | 2015 | 2019 | 2014 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.6, January 2023 | Apache Ignite 2.6 | cloud service with continuous releases | 2.10.0, May 2022 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Elastic License | Open Source Apache 2.0 | commercial | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C++, Java, .Net | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM | Linux OS X Solaris Windows | hosted | hosted | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free Flexible type definitions. Once a type is defined, it is persistent | yes | Fixed schema with schema-less datatypes (dynamic) | yes support of semi-structured data formats (JSON, XML, Avro) | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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, double, decimal, uuid, integer, blob, boolean, datetime | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes All search fields are automatically indexed | yes | all fields are automatically indexed | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | ANSI-99 for query and DML statements, subset of DDL | Kusto Query Language (KQL), SQL subset | yes | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Java API RESTful HTTP/JSON API | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | CLI Client JDBC ODBC | Open binary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby | C# C++ Java PHP Python Ruby Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | JavaScript (Node.js) Python | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes (compute grid and cache interceptors can be used instead) | Yes, possible languages: KQL, Python, R | user defined functions | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by using the 'percolation' feature | yes (cache interceptors and events) | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no similar concept for controling cloud resources | yes, before/after data modification events, on replication events, client session events | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding Implicit feature of the cloud service | yes | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | yes (replicated cache) | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | yes | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with Raft) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | ES-Hadoop Connector | yes (compute grid and hadoop accelerator) | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | no | ACID | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes, cooperative multitasking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes, write ahead logging | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | Memcached and Redis integration | yes | no | no | yes, full featured in-memory storage engine with persistence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Security Hooks for custom implementations | Azure Active Directory Authentication | Users with fine-grained authorization concept, user roles and pluggable authentication | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Elasticsearch | Ignite | Microsoft Azure Data Explorer | Snowflake | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2017 Elasticsearch moved into the top 10 most popular database management systems MySQL, PostgreSQL and Redis are the winners of the March ranking | Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | Data processing speed and reliability: in-memory synchronous replication Understanding Elasticsearch Reindexing: When to Reindex, Best Practices and Alternatives Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently The Total Economic Impact™️ of Elasticsearch 8 Powerful Alternatives to Elasticsearch Red Hat and Elastic Fuel Retrieval Augmented Generation for GenAI Use Cases provided by Google News GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 Apache Ignite: An Overview GridGain Releases Conference Schedule for Virtual Apache Ignite Summit 2023 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 Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Azure Data Explorer: Log and telemetry analytics benchmark Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog Microsoft Introduces Azure Integration Environments and Business Process Tracking in Public Preview provided by Google News Snowflake Stock: Is It A Buy Right Now? Here's What Earnings, SNOW Stock Chart Show Snowflake Unveils the Future of Enterprise AI, Apps, and Data at Sixth-Annual Data Cloud Summit Snowflake Data Clean Rooms Democratize Secure Data Sharing Across Clouds Snowflake’s Data Clean Room promises to ease analysis of PII data Infosys at Snowflake Data Cloud Summit 2024 provided by Google News In-Memory Showdown: Redis vs. Tarantool TaranHouse: New Big Data Warehouse Announced by Tarantool Deploying Tarantool Cartridge applications with zero effort (Part 1) Deploying Tarantool Cartridge applications with zero effort (Part 2) Тarantool Cartridge: Sharding Lua Backend in Three Lines provided by Google News |
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