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DBMS > atoti vs. Hazelcast vs. Qdrant vs. Tarantool

System Properties Comparison atoti vs. Hazelcast vs. Qdrant vs. Tarantool

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHazelcast  Xexclude from comparisonQdrant  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A widely adopted in-memory data gridA high-performance vector database with neural network or semantic-based matchingIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelObject oriented DBMSKey-value storeVector DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#11  Object oriented DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.28
Rank#167  Overall
#8  Vector DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteatoti.iohazelcast.comgithub.com/­qdrant/­qdrant
qdrant.tech
www.tarantool.io
Technical documentationdocs.atoti.iohazelcast.org/­imdg/­docsqdrant.tech/­documentationwww.tarantool.io/­en/­doc
DeveloperActiveViamHazelcastQdrantVK
Initial release200820212008
Current release5.3.6, November 20232.10.0, May 2022
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaRustC and C++
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
Windows
BSD
Linux
macOS
Data schemeschema-freeschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yes infothe object must implement a serialization strategynono
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like query languagenoFull-featured ANSI SQL support
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Open binary protocol
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresPythonyes infoEvent Listeners, Executor ServicesLua, C and SQL stored procedures
Triggersyes infoEventsyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapCollection-level replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency, tunable consistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlRole-based access controlKey-based authenticationAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
atotiHazelcastQdrantTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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