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

DBMS > Geode vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. Pinecone

System Properties Comparison Geode vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. Pinecone

Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platformA managed, cloud-native vector database
Primary database modelKey-value storeTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedVector DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Websitegeode.apache.orggithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorerwww.pinecone.io
Technical documentationgeode.apache.org/­docsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.pinecone.io/­docs/­overview
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.SpotifyLeanXcaleMicrosoftPinecone Systems, Inc
Initial release20022014201520192019
Current release1.1, February 2017cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedhosted
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesString, 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.nonoyesno
Secondary indexesnoyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (OQL)noyes infothrough Apache DerbyKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Python
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, R
Triggersyes infoCache Event Listenersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodenoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnoyesnono
User concepts infoAccess controlAccess rights per client and object definableAzure Active Directory Authentication

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
GeodeHeroicLeanXcaleMicrosoft Azure Data ExplorerPinecone
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

This is how much one of the most expensive gems costs at the Tucson gem show
11 February 2024, KGUN 9 Tucson News

Apache Geode Spawns 'All Sorts of In-Memory Things'
4 January 2017, The New Stack

Victor I. Cazares Wants NYTW to Call for Ceasefire in Gaza
22 February 2024, Vulture

Event-Driven Architectures with Apache Geode and Spring Integration
20 March 2019, InfoQ.com

1. Introduction to Pivotal GemFire In-Memory Data Grid and Apache Geode - Scaling Data Services with Pivotal ...
15 November 2018, oreilly.com

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Update records in a Kusto Database (public preview)
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink
8 January 2024, Microsoft

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ...
5 February 2024, Microsoft

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, Microsoft

provided by Google News

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions
12 June 2024, MarkTechPost

Pinecone launches its serverless vector database out of preview
12 June 2024, Yahoo Movies UK

Gathr Partners with Pinecone to Accelerate Generative AI Adoption
12 June 2024, ARC Advisory Group

Pinecone launches its serverless vector database out of preview
21 May 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.

Milvus logo

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

Present your product here