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DBMS > OpenEdge vs. QuestDB vs. Solr vs. Sphinx

System Properties Comparison OpenEdge vs. QuestDB vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameOpenEdge  Xexclude from comparisonQuestDB  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemA high performance open source SQL database for time series dataA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSTime Series DBMSSearch engineSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.progress.com/­openedgequestdb.iosolr.apache.orgsphinxsearch.com
Technical documentationdocumentation.progress.com/­output/­ua/­OpenEdge_latestquestdb.io/­docssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperProgress Software CorporationQuestDB Technology IncApache Software FoundationSphinx Technologies Inc.
Initial release1984201420062001
Current releaseOpenEdge 12.2, March 20209.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
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 languageJava (Zero-GC), C++, RustJavaC++
Server operating systemsAIX
HP-UX
Linux
Solaris
Windows
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingno
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.yesnoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLyes infoclose to SQL 92SQL with time-series extensionsSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesProgress proprietary ABL (Advanced Business Language)C 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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnoJava pluginsno
Triggersyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infosince Version 11.4horizontal partitioning (by timestamps)ShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with eventual consistencyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID for single-table writesoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 controlUsers and groupsyesno
More information provided by the system vendor
OpenEdgeQuestDBSolrSphinx
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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OpenEdgeQuestDBSolrSphinx
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