DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Cubrid vs. EXASOL vs. FeatureBase vs. Google Cloud Datastore vs. YottaDB

System Properties Comparison Cubrid vs. EXASOL vs. FeatureBase vs. Google Cloud Datastore vs. YottaDB

Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonEXASOL  Xexclude from comparisonFeatureBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast and solid embedded Key-value store
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitecubrid.com (korean)
cubrid.org (english)
www.exasol.comwww.featurebase.comcloud.google.com/­datastoreyottadb.com
Technical documentationcubrid.org/­manualswww.exasol.com/­resourcesdocs.featurebase.comcloud.google.com/­datastore/­docsyottadb.com/­resources/­documentation
DeveloperCUBRID Corporation, CUBRID FoundationExasolMolecula and Pilosa Open Source ContributorsGoogleYottaDB, LLC
Initial release20082000201720082001
Current release11.0, January 20212022, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaGoC
Server operating systemsLinux
Windows
Linux
macOS
hostedDocker
Linux
Data schemeyesyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details hereno
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.nonononono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesyesSQL queriesSQL-like query language (GQL)by using the Octo plugin
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
.Net
JDBC
ODBC
WebSocket
gRPC
JDBC
Kafka Connector
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Lua
Python
R
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsusing Google App Engine
TriggersyesyesnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyesyesyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users and groups based on OS-security mechanisms

More information provided by the system vendor

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

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

More resources
CubridEXASOLFeatureBaseGoogle Cloud DatastoreYottaDB
Recent citations in the news

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
14 May 2024, insideBIGDATA

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series
21 May 2024, Unite.AI

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
22 February 2024, AiThority

provided by Google News

Get Your Infrastructure Ready for Real-Time Analytics
8 March 2022, Built In

Pilosa: A Scalable High Performance Bitmap Database Index
17 June 2019, hackernoon.com

The 10 Coolest Big Data Tools Of 2021
7 December 2021, CRN

32 Data and Analytics Startups That Will Go Big, According to VCs
28 September 2021, Business Insider

provided by Google News

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
4 June 2024, TechRadar

Inside Google’s strategic move to eliminate customer cloud data transfer fees
12 January 2024, Network World

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

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