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DBMS > Apache Impala vs. Graph Engine vs. MySQL vs. Vertica vs. Yaacomo

System Properties Comparison Apache Impala vs. Graph Engine vs. MySQL vs. Vertica vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMySQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineWidely used open source RDBMSCloud 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 DBMSGraph DBMS
Key-value store
Relational DBMS infoKey/Value like access via memcached APIRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteimpala.apache.orgwww.graphengine.iowww.mysql.comwww.vertica.comyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.graphengine.io/­docs/­manualdev.mysql.com/­docvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftOracle infosince 2010, originally MySQL AB, then SunOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release20132010199520052009
Current release4.1.0, June 20228.4.0, April 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availablecommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageC++.NET and CC and C++C++
Server operating systemsLinux.NETFreeBSD
Linux
OS X
Solaris
Windows
LinuxAndroid
Linux
Windows
Data schemeyesyesyesYes, 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 dateyesyesyesyesyes
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.nonoyesnono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith proprietary extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
F#
Visual Basic
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes infoproprietary syntaxyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyesyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabrichorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-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 methodsyes infoquery execution via MapReducenono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infonot for MyISAM storage engineACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept infono user groups or rolesfine 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
Apache ImpalaGraph Engine infoformer name: TrinityMySQLVertica 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...
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More resources
Apache ImpalaGraph Engine infoformer name: TrinityMySQLVertica infoOpenText™ Vertica™Yaacomo
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