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DBMS > Splice Machine vs. Tibero vs. Vertica

System Properties Comparison Splice Machine vs. Tibero vs. Vertica

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Editorial information provided by DB-Engines
NameSplice Machine  Xexclude from comparisonTibero  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA secure RDBMS, designed for easy portability from OracleCloud 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 DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score1.78
Rank#140  Overall
#64  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitesplicemachine.comus.tmaxsoft.com/­products/­tiberowww.vertica.com
Technical documentationsplicemachine.com/­how-it-workstechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.htmlvertica.com/­documentation
DeveloperSplice MachineTmaxSoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201420032005
Current release3.1, March 20216, April 201512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL 3.0, commercial license availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 AssemblerC++
Server operating systemsLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Linux
Data schemeyesyesYes, 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 dateyesyesyes
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.yesno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoJavaPersistent Stored Procedure (PSM)yes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning infoby range, hash, list or compositehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-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 methodsYes, via Full Spark Integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno infoplanned for next versionno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard (SQL 92, SQL 99)fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Splice MachineTiberoVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Splice MachineTiberoVertica infoOpenText™ Vertica™
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