DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Hive vs. Microsoft Azure Cosmos DB vs. SingleStore vs. Tkrzw vs. Trafodion

System Properties Comparison Hive vs. Microsoft Azure Cosmos DB vs. SingleStore vs. Tkrzw vs. Trafodion

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopGlobally distributed, horizontally scalable, multi-model database serviceMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score5.38
Rank#62  Overall
#35  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitehive.apache.orgazure.microsoft.com/­services/­cosmos-dbwww.singlestore.comdbmx.net/­tkrzwtrafodion.apache.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homelearn.microsoft.com/­azure/­cosmos-dbdocs.singlestore.comtrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoinitially developed by FacebookMicrosoftSingleStore Inc.Mikio HirabayashiApache Software Foundation, originally developed by HP
Initial release20122014201320202014
Current release3.1.3, April 20228.5, January 20240.9.3, August 20202.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree developer edition availableOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaC++, GoC++C++, Java
Server operating systemsAll OS with a Java VMhostedLinux info64 bit version requiredLinux
macOS
Linux
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON typesyesnoyes
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 indexesyesyes infoAll properties auto-indexed by defaultyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes infobut no triggers and foreign keysnoyes
APIs and other access methodsJDBC
ODBC
Thrift
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJavaScriptyesnoJava Stored Procedures
TriggersnoJavaScriptnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infohash partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud serviceSource-replica replication infostores two copies of each physical data partition on two separate nodesnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducewith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no infocan define user-defined aggregate functions for map-reduce-style calculationsnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-item ACID transactions with snapshot isolation within a partitionACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing specific database classesno
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights can be defined down to the item levelFine grained access control via users, groups and rolesnofine grained access rights according to SQL-standard
More information provided by the system vendor
HiveMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSingleStore infoformer name was MemSQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTrafodion
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
HiveMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSingleStore infoformer name was MemSQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTrafodion
DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

show all

Recent citations in the news

Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore ...
10 June 2024, AWS Blog

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

Public Preview: DiskANN vector indexing and search in Azure Cosmos DB NoSQL | Azure updates
21 May 2024, azure.microsoft.com

Start your AI journey with Microsoft Azure Cosmos DB—compete for $10K
9 May 2024, azure.microsoft.com

Public Preview: vCore-based Azure Cosmos DB for MongoDB cross-region disaster recovery (DR) | Azure updates
21 May 2024, azure.microsoft.com

Building Planet-Scale .NET Apps with Azure Cosmos DB
4 June 2024, Visual Studio Magazine

Public preview: Change partition key of a container in Azure Cosmos DB (NoSQL API) | Azure updates
27 March 2024, azure.microsoft.com

provided by Google News

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development
24 January 2024, Business Wire

SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files
29 January 2024, Blocks and Files

Announcing watsonx.ai and SingleStore for generative AI applications
15 November 2023, IBM

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here