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DBMS > atoti vs. BigObject vs. GridDB vs. Vertica

System Properties Comparison atoti vs. BigObject vs. GridDB vs. Vertica

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBigObject  Xexclude from comparisonGridDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Analytic DBMS for real-time computations and queriesScalable in-memory time series database optimized for IoT and Big DataCloud 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 DBMSRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteatoti.iobigobject.iogriddb.netwww.vertica.com
Technical documentationdocs.atoti.iodocs.bigobject.iodocs.griddb.netvertica.com/­documentation
DeveloperActiveViamBigObject, Inc.Toshiba CorporationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201520132005
Current release5.1, August 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercial infofree community edition availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial 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

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Implementation languageJavaC++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux
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 dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresPythonLuanoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-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 methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes infoRead/write lock on objects (tables, trees)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.yesyesyesno
User concepts infoAccess controlnoAccess rights for users can be defined per databasefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
atotiBigObjectGridDBVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
atotiBigObjectGridDBVertica infoOpenText™ Vertica™
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