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DBMS > Hive vs. NuoDB vs. Splice Machine vs. Vertica vs. WakandaDB

System Properties Comparison Hive vs. NuoDB vs. Splice Machine vs. Vertica vs. WakandaDB

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonNuoDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWakandaDB  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopNuoDB is a webscale distributed database that supports SQL and ACID transactionsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkCloud 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.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS infoColumn orientedObject oriented DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.94
Rank#197  Overall
#92  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitehive.apache.orgwww.3ds.com/­nuodb-distributed-sql-databasesplicemachine.comwww.vertica.comwakanda.github.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedoc.nuodb.comsplicemachine.com/­how-it-worksvertica.com/­documentationwakanda.github.io/­doc
DeveloperApache Software Foundation infoinitially developed by FacebookDassault Systèmes infooriginally NuoDB, Inc.Splice MachineOpenText infopreviously Micro Focus and Hewlett PackardWakanda SAS
Initial release20122013201420052012
Current release3.1.3, April 20223.1, March 202112.0.3, January 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoAGPL 3.0, commercial license availablecommercial infoLimited community edition freeOpen Source infoAGPLv3, extended commercial license available
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

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Implementation languageJavaC++JavaC++C++, JavaScript
Server operating systemsAll OS with a Java VMhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
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.nonono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsJDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
RESTful HTTP API
Supported programming languagesC++
Java
PHP
Python
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava, SQLyes infoJavayes, PostgreSQL PL/pgSQL, with minor differencesyes
Triggersnoyesyesyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardingdata is dynamically stored/cached on the nodes where it is read/writtenShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoManaged transparently by NuoDBMulti-source replication
Source-replica replication
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoYes, via Full Spark Integrationno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infotunable commit protocolACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTemporary tableyesnono
User concepts infoAccess controlAccess rights for users, groups and rolesStandard SQL roles/ privileges, Administrative UsersAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashyes
More information provided by the system vendor
HiveNuoDBSplice MachineVertica infoOpenText™ Vertica™WakandaDB
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
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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HiveNuoDBSplice MachineVertica infoOpenText™ Vertica™WakandaDB
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