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DBMS > Drizzle vs. Milvus vs. QuestDB vs. Teradata Aster

System Properties Comparison Drizzle vs. Milvus vs. QuestDB vs. Teradata Aster

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonMilvus  Xexclude from comparisonQuestDB  Xexclude from comparisonTeradata Aster  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.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A DBMS designed for efficient storage of vector data and vector similarity searchesA high performance open source SQL database for time series dataPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSVector DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitemilvus.ioquestdb.io
Technical documentationmilvus.io/­docs/­overview.mdquestdb.io/­docs
DeveloperDrizzle project, originally started by Brian AkerQuestDB Technology IncTeradata
Initial release2008201920142005
Current release7.2.4, September 20122.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++C++, GoJava (Zero-GC), C++, Rust
Server operating systemsFreeBSD
Linux
OS X
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Linux
Data schemeyesyes infoschema-free via InfluxDB Line ProtocolFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesyes
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.nonoyes infoin Aster File Store
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL with time-series extensionsyes
APIs and other access methodsJDBCRESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C++
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnononoR packages
Triggersno infohooks for callbacks inside the server can be used.nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication with eventual consistencyyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID for single-table writesACID
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.yesyes infothrough memory mapped filesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
DrizzleMilvusQuestDBTeradata Aster
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Relational model with native time series support Column-based storage and time partitioned...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
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Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
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More resources
DrizzleMilvusQuestDBTeradata Aster
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