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DBMS > Apache Druid vs. IBM Db2 Event Store vs. Microsoft Access vs. Vertica

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. Microsoft Access vs. Vertica

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Event Store optimized for Internet of Things use casesMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­accesswww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­accessvertica.com/­documentation
DeveloperApache Software Foundation and contributorsIBMMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201719922005
Current release29.0.1, April 20242.01902 (16.0.11328.20222), March 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree developer edition availablecommercial infoBundled with Microsoft Officecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++C++
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionWindows infoNot a real database server, but making use of DLLsLinux
Data schemeyes infoschema-less columns are supportedyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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.nonono
Secondary indexesyesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standardFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyes infosince Access 2010 using the ACE-engineyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infosince Access 2010 using the ACE-engineyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive-active shard replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infobut no files for transaction loggingACID
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 storageyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DruidIBM Db2 Event StoreMicrosoft AccessVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Apache DruidIBM Db2 Event StoreMicrosoft AccessVertica infoOpenText™ Vertica™
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