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DBMS > Apache Impala vs. IBM Db2 Event Store vs. NSDb vs. PostgreSQL

System Properties Comparison Apache Impala vs. IBM Db2 Event Store vs. NSDb vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonNSDb  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed Event Store optimized for Internet of Things use casesScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Time Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument storeDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score644.36
Rank#4  Overall
#4  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­db2-event-storensdb.iowww.postgresql.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ibm.com/­docs/­en/­db2-event-storensdb.io/­Architecturewww.postgresql.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2013201720171989 info1989: Postgres, 1996: PostgreSQL
Current release4.1.0, June 20222.016.4, August 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree developer edition availableOpen Source infoApache Version 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++Java, ScalaC
Server operating systemsLinuxLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeSQL-like query languageyes infostandard with numerous extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive-active shard replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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-standard

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More resources
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