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DBMS > ObjectBox vs. Sphinx vs. Splice Machine vs. TDengine vs. Vertica

System Properties Comparison ObjectBox vs. Sphinx vs. Splice Machine vs. TDengine vs. Vertica

Editorial information provided by DB-Engines
NameObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTDengine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionExtremely fast embedded database for small devices, IoT and MobileOpen 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 SparkTime Series DBMS and big data platformCloud 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 modelObject oriented DBMSSearch engineRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsTime Series DBMSRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteobjectbox.iosphinxsearch.comsplicemachine.comgithub.com/­taosdata/­TDengine
tdengine.com
www.vertica.com
Technical documentationdocs.objectbox.iosphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.tdengine.comvertica.com/­documentation
DeveloperObjectBox LimitedSphinx Technologies Inc.Splice MachineTDEngine, previously Taos DataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20172001201420192005
Current release3.5.1, February 20233.1, March 20213.0, August 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL V3, also commercial editions 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++JavaCC++
Server operating systemsAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
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 dateyesnoyesyesyes
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 indexesyesyes infofull-text index on all search fieldsyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)yesStandard SQL with extensions for time-series applicationsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsProprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
JDBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes infoJavanoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyesyes, via alarm monitoringyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesonline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
yesMulti-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 methodsnonoYes, via Full Spark Integrationno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
ObjectBoxSphinxSplice MachineTDengineVertica infoOpenText™ Vertica™
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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