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DBMS > Apache Impala vs. QuestDB vs. Solr vs. Sqrrl

System Properties Comparison Apache Impala vs. QuestDB vs. Solr vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonQuestDB  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopA high performance open source SQL database for time series dataA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSTime Series DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument storeRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgquestdb.iosolr.apache.orgsqrrl.com
Technical documentationimpala.apache.org/­impala-docs.htmlquestdb.io/­docssolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaQuestDB Technology IncApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2013201420062012
Current release4.1.0, June 20229.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustJavaJava
Server operating systemsLinuxLinux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.nonoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL with time-series extensionsSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)ShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with eventual consistencyyesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID for single-table writesoptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
Apache ImpalaQuestDBSolrSqrrl
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache ImpalaQuestDBSolrSqrrl
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