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DBMS > Apache Impala vs. EDB Postgres vs. QuestDB vs. Vitess

System Properties Comparison Apache Impala vs. EDB Postgres vs. QuestDB vs. Vitess

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEDB Postgres  Xexclude from comparisonQuestDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.A high performance open source SQL database for time series dataScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Relational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteimpala.apache.orgwww.enterprisedb.comquestdb.iovitess.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.enterprisedb.com/­docsquestdb.io/­docsvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEnterpriseDBQuestDB Technology IncThe Linux Foundation, PlanetScale
Initial release2013200520142013
Current release4.1.0, June 202214, December 202115.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoBSD for PostgreSQL-componentsOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava (Zero-GC), C++, RustGo
Server operating systemsLinuxLinux
Windows
Linux
macOS
Windows
Docker
Linux
macOS
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard with numerous extensionsSQL with time-series extensionsyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoproprietary syntax
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or rangehorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationSource-replica replication with eventual consistencyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID for single-table writesACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infotable locks or row locks depending on storage engine
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.nonoyes infothrough memory mapped filesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Apache ImpalaEDB PostgresQuestDBVitess
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 ImpalaEDB PostgresQuestDBVitess
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