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DBMS > Infobright vs. LeanXcale vs. Vertica vs. Yaacomo

System Properties Comparison Infobright vs. LeanXcale vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameInfobright  Xexclude from comparisonLeanXcale  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.00
Rank#193  Overall
#90  Relational DBMS
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websiteignitetech.com/­softwarelibrary/­infobrightdbwww.leanxcale.comwww.vertica.comyaacomo.com
Technical documentationvertica.com/­documentation
DeveloperIgnite Technologies Inc.; formerly InfoBright Inc.LeanXcaleOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2005201520052009
Current release12.0.3, January 2023
License infoCommercial or Open Sourcecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercialcommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemsLinux
Windows
LinuxAndroid
Linux
Windows
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
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.nonono
Secondary indexesno infoKnowledge Grid Technology used insteadNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLyesyes infothrough Apache DerbyFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
InfobrightLeanXcaleVertica infoOpenText™ Vertica™Yaacomo
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...
» more

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More resources
InfobrightLeanXcaleVertica infoOpenText™ Vertica™Yaacomo
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