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DBMS > Apache Druid vs. Databend vs. Elasticsearch vs. Quasardb vs. Vertica

System Properties Comparison Apache Druid vs. Databend vs. Elasticsearch vs. Quasardb vs. Vertica

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabend  Xexclude from comparisonElasticsearch  Xexclude from comparisonQuasardb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn 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 metricDistributed, high-performance timeseries databaseCloud 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 modelRelational DBMS
Time Series DBMS
Relational DBMSSearch engineTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitedruid.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.elastic.co/­elasticsearchquasar.aiwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databend.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldoc.quasar.ai/­mastervertica.com/­documentation
DeveloperApache Software Foundation and contributorsDatabend LabsElasticquasardbOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122021201020092005
Current release29.0.1, April 20241.0.59, April 20238.6, January 20233.14.1, January 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoElastic Licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJavaC++C++
Server operating systemsLinux
OS X
Unix
hosted
Linux
macOS
All OS with a Java VMBSD
Linux
OS X
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binaryyes
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.nonononono
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes infowith tagsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingyesSQL-like query languageSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
CLI Client
JDBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infoby using the 'percolation' featurenoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingSharding infoconsistent hashinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyesSource-replica replication with selectable replication factorMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoES-Hadoop Connectorwith Hadoop integrationno infoBi-directional Spark integration
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, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyes infoTransient modeno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers with fine-grained authorization concept, user rolesCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DruidDatabendElasticsearchQuasardbVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Apache DruidDatabendElasticsearchQuasardbVertica infoOpenText™ Vertica™
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