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DBMS > Apache Impala vs. atoti vs. BoltDB vs. Vertica

System Properties Comparison Apache Impala vs. atoti vs. BoltDB vs. Vertica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonatoti  Xexclude from comparisonBoltDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.An embedded key-value store for Go.Cloud 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 DBMSObject oriented DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.80
Rank#215  Overall
#31  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteimpala.apache.orgatoti.iogithub.com/­boltdb/­boltwww.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.atoti.iovertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaActiveViamOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320132005
Current release4.1.0, June 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree versions availableOpen Source infoMIT Licensecommercial 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 languageC++JavaGoC++
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeYes, 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 dateyesnoyes
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 indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsMultidimensional Expressions (MDX)noFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBCGoC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducePythonnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-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 infoquery execution via MapReducenonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyes, 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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaatotiBoltDBVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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Apache ImpalaatotiBoltDBVertica infoOpenText™ Vertica™
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