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DBMS > Apache Pinot vs. ArangoDB vs. YugabyteDB

System Properties Comparison Apache Pinot vs. ArangoDB vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonArangoDB  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Search engine
Relational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score3.32
Rank#90  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitepinot.apache.orgarangodb.comwww.yugabyte.com
Technical documentationdocs.pinot.apache.orgdocs.arangodb.comdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
Social network pagesLinkedInTwitterFacebookYouTubeInstagram
DeveloperApache Software Foundation and contributorsArangoDB Inc.Yugabyte Inc.
Initial release201520122017
Current release1.0.0, September 20233.11.5, November 20232.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial license (Enterprise) availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageJavaC++C and C++
Server operating systemsAll OS with a Java JDK11 or higherLinux
OS X
Windows
Linux
OS X
Data schemeyesschema-free infoautomatically recognizes schema within a collectiondepending on used data model
Typing infopredefined data types such as float or dateyesyes infostring, double, boolean, list, hashyes
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.no
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes, PostgreSQL compatible
APIs and other access methodsJDBCAQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesGo
Java
Python
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresJavaScriptyes infosql, plpgsql, C
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infosince version 2.0Hash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with configurable replication factorBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infocan be done with stored procedures in JavaScriptno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyesyes
More information provided by the system vendor
Apache PinotArangoDBYugabyteDB
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Systems of record and engagement for cloud native applications that require resilience,...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more
Apache 2.0 license for the database
» more

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More resources
Apache PinotArangoDBYugabyteDB
DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

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