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DBMS > Databend vs. IBM Db2 Event Store vs. Microsoft Access vs. Sphinx vs. Vertica

System Properties Comparison Databend vs. IBM Db2 Event Store vs. Microsoft Access vs. Sphinx vs. Vertica

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSphinx  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDistributed 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.)Open source search engine for searching in data from different sources, e.g. relational databasesCloud 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 DBMSEvent Store
Time Series DBMS
Relational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.comwww.vertica.com
Technical documentationdocs.databend.comwww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­accesssphinxsearch.com/­docsvertica.com/­documentation
DeveloperDatabend LabsIBMMicrosoftSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20212017199220012005
Current release1.0.59, April 20232.01902 (16.0.11328.20222), March 20193.5.1, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial infoBundled with Microsoft OfficeOpen Source infoGPL version 2, commercial licence availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono 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 languageRustC and C++C++C++C++
Server operating systemshosted
Linux
macOS
Linux infoLinux, macOS, Windows for the developer additionWindows infoNot a real database server, but making use of DLLsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesYes, 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 dateyesyesyesnoyes
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 indexesnonoyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standardSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
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++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyes infosince Access 2010 using the ACE-enginenoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infosince Access 2010 using the ACE-enginenoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneActive-active shard replicationnonenoneMulti-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 methodsnonononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infobut no files for transaction loggingnoACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
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 infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003nofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatabendIBM Db2 Event StoreMicrosoft AccessSphinxVertica 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...
» more
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...
» more

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More resources
DatabendIBM Db2 Event StoreMicrosoft AccessSphinxVertica infoOpenText™ Vertica™
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