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

DBMS > BoltDB vs. Hawkular Metrics vs. NSDb vs. Pinecone

System Properties Comparison BoltDB vs. Hawkular Metrics vs. NSDb vs. Pinecone

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonNSDb  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA managed, cloud-native vector database
Primary database modelKey-value storeTime Series DBMSTime Series DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitegithub.com/­boltdb/­boltwww.hawkular.orgnsdb.iowww.pinecone.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidensdb.io/­Architecturedocs.pinecone.io/­docs/­overview
DeveloperCommunity supported by Red HatPinecone Systems, Inc
Initial release2013201420172019
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaJava, Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
macOS
hosted
Data schemeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyes: int, bigint, decimal, stringString, Number, Boolean
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 indexesnonoall fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like query languageno
APIs and other access methodsHTTP RESTgRPC
HTTP REST
WebSocket
RESTful HTTP API
Supported programming languagesGoGo
Java
Python
Ruby
Java
Scala
Python
Server-side scripts infoStored proceduresnonono
Triggersnoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnono

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
BoltDBHawkular MetricsNSDbPinecone
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

4 Instructive Postmortems on Data Downtime and Loss
1 March 2024, The Hacker News

Grafana Loki: Architecture Summary and Running in Kubernetes
14 March 2023, hackernoon.com

Roblox’s cloud-native catastrophe: A post mortem
31 January 2022, InfoWorld

How to Put a GUI on Ansible, Using Semaphore
22 April 2023, The New Stack

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

Pinecone: New vector database architecture a 'breakthrough' to curb AI hallucinations
16 January 2024, VentureBeat

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

Pinecone’s vector database gets a new serverless architecture
16 January 2024, TechCrunch

provided by Google News



Share this page

Featured Products

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.

AllegroGraph logo

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

Milvus logo

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

RaimaDB logo

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

Present your product here