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DBMS > Badger vs. Hazelcast vs. Trafodion vs. Vertica

System Properties Comparison Badger vs. Hazelcast vs. Trafodion vs. Vertica

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHazelcast  Xexclude from comparisonTrafodion  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A widely adopted in-memory data gridTransactional SQL-on-Hadoop DBMSCloud 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 modelKey-value storeKey-value storeRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerhazelcast.comtrafodion.apache.orgwww.vertica.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerhazelcast.org/­imdg/­docstrafodion.apache.org/­documentation.htmlvertica.com/­documentation
DeveloperDGraph LabsHazelcastApache Software Foundation, originally developed by HPOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017200820142005
Current release5.3.6, November 20232.3.0, February 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial 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 languageGoJavaC++, JavaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinuxLinux
Data schemeschema-freeschema-freeyesYes, 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 datenoyesyesyes
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.noyes infothe object must implement a serialization strategynono
Secondary indexesnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesJava Stored Proceduresyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infoEventsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoReplicated Mapyes, via HBaseMulti-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 methodsnoyesyes infovia user defined functions and HBaseno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedACIDACID
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.noyesnono
User concepts infoAccess controlnoRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BadgerHazelcastTrafodionVertica 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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More resources
BadgerHazelcastTrafodionVertica infoOpenText™ Vertica™
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