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DBMS > Microsoft Access vs. Pinecone vs. QuestDB vs. Sphinx vs. Splice Machine

System Properties Comparison Microsoft Access vs. Pinecone vs. QuestDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameMicrosoft Access  Xexclude from comparisonPinecone  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMicrosoft 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.)A managed, cloud-native vector databaseA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSVector DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score93.76
Rank#12  Overall
#8  Relational DBMS
Score3.02
Rank#87  Overall
#3  Vector DBMS
Score2.81
Rank#98  Overall
#7  Time Series DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitewww.microsoft.com/­en-us/­microsoft-365/­accesswww.pinecone.ioquestdb.iosphinxsearch.comsplicemachine.com
Technical documentationdeveloper.microsoft.com/­en-us/­accessdocs.pinecone.io/­docs/­overviewquestdb.io/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperMicrosoftPinecone Systems, IncQuestDB Technology IncSphinx Technologies Inc.Splice Machine
Initial release19922019201420012014
Current release1902 (16.0.11328.20222), March 20193.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustC++Java
Server operating systemsWindows infoNot a real database server, but making use of DLLshostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyesyes
Typing infopredefined data types such as float or dateyesString, Number, Booleanyesnoyes
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.nono
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infobut not compliant to any SQL standardnoSQL with time-series extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET
DAO
ODBC
OLE DB
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
PythonC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infosince Access 2010 using the ACE-enginenonoyes infoJava
Triggersyes infosince Access 2010 using the ACE-enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with eventual consistencynoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infobut no files for transaction loggingACID for single-table writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infobut no files for transaction loggingyesyesyes 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.noyes infothrough memory mapped filesyes
User concepts infoAccess controlno infoa simple user-level security was built in till version Access 2003noAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Microsoft AccessPineconeQuestDBSphinxSplice Machine
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