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DBMS > Apache Impala vs. Brytlyt vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Synapse Analytics vs. Yaacomo

System Properties Comparison Apache Impala vs. Brytlyt vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Synapse Analytics vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websiteimpala.apache.orgbrytlyt.iowww.postgresql.fastware.comazure.microsoft.com/­services/­synapse-analyticsyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iowww.postgresql.fastware.com/­product-manualsdocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyMicrosoftQ2WEB GmbH
Initial release2013201620162009
Current release4.1.0, June 20225.0, August 2023Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++ and CUDACC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
Windows
hostedAndroid
Linux
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
Java
PHP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLuser defined functionsTransact SQL
Triggersnoyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashSharding, horizontal partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaBrytlytFujitsu Enterprise PostgresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseYaacomo
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Apache ImpalaBrytlytFujitsu Enterprise PostgresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseYaacomo
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