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

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

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Editorial information provided by DB-Engines
NameObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonVertica infoVertica Analytics Platform  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 SparkColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelObject oriented DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.65
Rank#208  Overall
#11  Object oriented DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Score0.79
Rank#186  Overall
#91  Relational DBMS
Score21.77
Rank#31  Overall
#18  Relational DBMS
Websiteobjectbox.iosphinxsearch.comsplicemachine.comwww.vertica.com
Technical documentationdocs.objectbox.iosphinxsearch.com/­docsdoc.splicemachine.comwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperObjectBox LimitedSphinx Technologies Inc.Splice MachineVertica / Micro Focus infoprior to that Hewlett Packard
Initial release2017200120142005
Current release3.2.1, January 20202.0Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++Java
Server operating systemsAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesnoyesyes
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.noyes
Secondary indexesyesyes infofull-text index on all search fieldsyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)yesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsProprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
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++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnonoyes infoJavayes
Triggersnonoyesno
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 PartitioningSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesonline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
Multi-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
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)yes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
ObjectBoxSphinxSplice MachineVertica infoVertica Analytics Platform
Specific characteristicsTHE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesOperational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosNew AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Communication 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 modelsKubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
Cost-based models and subscription-based models are available
» more
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