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DBMS > Apache Doris vs. Databend vs. Elasticsearch

System Properties Comparison Apache Doris vs. Databend vs. Elasticsearch

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonDatabend  Xexclude from comparisonElasticsearch  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric
Primary database modelRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Websitedoris.apache.org
github.com/­apache/­doris
github.com/­datafuselabs/­databend
www.databend.com
www.elastic.co/­elasticsearch
Technical documentationgithub.com/­apache/­doris/­wikidocs.databend.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
DeveloperApache Software Foundation, originally contributed from BaiduDatabend LabsElastic
Initial release201720212010
Current release1.2.2, February 20231.0.59, April 20238.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoElastic License
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaRustJava
Server operating systemsLinuxhosted
Linux
macOS
All OS with a Java VM
Data schemeyesyesschema-free infoFlexible type definitions. Once a type is defined, it is persistent
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesSQL-like query language
APIs and other access methodsJDBC
MySQL client
CLI Client
JDBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesJavaGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyes
Triggersnonoyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoES-Hadoop Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integration
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user roles

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Apache DorisDatabendElasticsearch
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Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

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24 June 2022, InfoWorld

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