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DBMS > Badger vs. Datomic vs. HugeGraph vs. Vertica

System Properties Comparison Badger vs. Datomic vs. HugeGraph vs. Vertica

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatomic  Xexclude from comparisonHugeGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA fast-speed and highly-scalable Graph 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 storeRelational DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datomic.comgithub.com/­hugegraph
hugegraph.apache.org
www.vertica.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comhugegraph.apache.org/­docsvertica.com/­documentation
DeveloperDGraph LabsCognitectBaiduOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201220182005
Current release1.0.7075, December 20230.912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freeOpen Source infoApache Version 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 languageGoJava, ClojureJavaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
macOS
Unix
Linux
Data schemeschema-freeyesyesYes, 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.nononono
Secondary indexesnoyesyes infoalso supports composite index and range indexNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnononoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGoClojure
Java
Groovy
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsasynchronous Gremlin script jobsyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoBy using transaction functionsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and 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 methodsnonovia hugegraph-sparkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnonoUsers, roles and permissionsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BadgerDatomicHugeGraphVertica 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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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BadgerDatomicHugeGraphVertica infoOpenText™ Vertica™
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