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 > Apache Pinot vs. Hyprcubd vs. KeyDB vs. Netezza

System Properties Comparison Apache Pinot vs. Hyprcubd vs. KeyDB vs. Netezza

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonHyprcubd  Xexclude from comparisonKeyDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyServerless Time Series DBMSAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitepinot.apache.orghyprcubd.com (offline)github.com/­Snapchat/­KeyDB
keydb.dev
www.ibm.com/­products/­netezza
Technical documentationdocs.pinot.apache.orgdocs.keydb.dev
DeveloperApache Software Foundation and contributorsHyprcubd, Inc.EQ Alpha Technology Ltd.IBM
Initial release201520192000
Current release1.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++
Server operating systemsAll OS with a Java JDK11 or higherhostedLinuxLinux infoincluded in appliance
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infotime, int, uint, float, stringpartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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.nono
Secondary indexesnoyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenoyes
APIs and other access methodsJDBCgRPC (https)Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
OLE DB
Supported programming languagesGo
Java
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoLuayes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datanoyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controltoken accesssimple password-based access control and ACLUsers with fine-grained authorization concept

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
Apache PinotHyprcubdKeyDBNetezza infoAlso called PureData System for Analytics by IBM
Recent citations in the news

Real-Time Analytics Solution for Usage-Based API Billing and Metering
8 May 2024, Towards Data Science

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

How Uber Accomplishes Job Counting At Scale
22 May 2024, Uber

StarTree Makes Observability Case for Apache Pinot Database
8 May 2024, DevOps.com

provided by Google News

Oh, snap! Snap snaps up database developer KeyDB
12 May 2022, TechCrunch

Snap Acquires KeyDB for Open-Source Services
17 May 2022, XR Today

Garnet–open-source faster cache-store speeds up applications, services
18 March 2024, microsoft.com

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Microsoft open-sources Garnet cache-store -- a Redis rival?
19 March 2024, The Stack

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

Netezza Performance Server
12 August 2020, IBM

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

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB 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

Neo4j logo

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

Present your product here