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DBMS > BigObject vs. Linter vs. Tarantool vs. Vertica

System Properties Comparison BigObject vs. Linter vs. Tarantool vs. Vertica

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonLinter  Xexclude from comparisonTarantool  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesRDBMS for high security requirementsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsCloud 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 DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMS infowith Tarantool/GIS extensionSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitebigobject.iolinter.ruwww.tarantool.iowww.vertica.com
Technical documentationdocs.bigobject.iowww.tarantool.io/­en/­docvertica.com/­documentation
DeveloperBigObject, Inc.relex.ruVKOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015199020082005
Current release2.10.0, May 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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 and C++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
BSD
Linux
macOS
Linux
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsYes, 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 dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.nononono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyesFull-featured ANSI SQL supportFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Open binary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresLuayes infoproprietary syntax with the possibility to convert from PL/SQLLua, C and SQL stored proceduresyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, before/after data modification events, on replication events, client session eventsyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.horizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BigObjectLinterTarantoolVertica 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...
» more
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
BigObjectLinterTarantoolVertica infoOpenText™ Vertica™
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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