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DBMS > Drizzle vs. Google Cloud Bigtable vs. Hazelcast vs. Pinecone

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Hazelcast vs. Pinecone

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonPinecone  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridA managed, cloud-native vector database
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeVector DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.23
Rank#92  Overall
#2  Vector DBMS
Websitecloud.google.com/­bigtablehazelcast.comwww.pinecone.io
Technical documentationcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsdocs.pinecone.io/­docs/­overview
DeveloperDrizzle project, originally started by Brian AkerGoogleHazelcastPinecone Systems, Inc
Initial release2008201520082019
Current release7.2.4, September 20125.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsFreeBSD
Linux
OS X
hostedAll OS with a Java VMhosted
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesString, 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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like query languageno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Python
Server-side scripts infoStored proceduresnonoyes infoEvent Listeners, Executor Services
Triggersno infohooks for callbacks inside the server can be used.noyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
DrizzleGoogle Cloud BigtableHazelcastPinecone
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