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DBMS > Dgraph vs. Hawkular Metrics vs. Qdrant vs. Tarantool

System Properties Comparison Dgraph vs. Hawkular Metrics vs. Qdrant vs. Tarantool

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Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonQdrant  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A 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 modelGraph DBMSTime Series DBMSVector DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitedgraph.iowww.hawkular.orggithub.com/­qdrant/­qdrant
qdrant.tech
www.tarantool.io
Technical documentationdgraph.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guideqdrant.tech/­documentationwww.tarantool.io/­en/­doc
DeveloperDgraph Labs, Inc.Community supported by Red HatQdrantVK
Initial release2016201420212008
Current release2.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open 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 languageGoJavaRustC and C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Windows
BSD
Linux
macOS
Data schemeschema-freeschema-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 dateyesyesNumbers, 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.nononono
Secondary indexesyesnoyes infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLnononoFull-featured ANSI SQL support
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
HTTP RESTgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Open binary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoLua, C and SQL stored procedures
Triggersnoyes infovia Hawkular Alertingyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesyesSharding infobased on CassandraShardingSharding, 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 nodesSynchronous replication via Raftselectable replication factor infobased on CassandraCollection-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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual 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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlno infoPlanned for future releasesnoKey-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
DgraphHawkular MetricsQdrantTarantool
DB-Engines blog posts

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

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