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DBMS > Bangdb vs. Milvus vs. Newts vs. Splice Machine

System Properties Comparison Bangdb vs. Milvus vs. Newts vs. Splice Machine

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonMilvus  Xexclude from comparisonNewts  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA DBMS designed for efficient storage of vector data and vector similarity searchesTime Series DBMS based on CassandraOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Vector DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitebangdb.commilvus.ioopennms.github.io/­newtssplicemachine.com
Technical documentationdocs.bangdb.commilvus.io/­docs/­overview.mdgithub.com/­OpenNMS/­newts/­wikisplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBOpenNMS GroupSplice Machine
Initial release2012201920142014
Current releaseBangDB 2.0, October 20212.3.4, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
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++C++, GoJavaJava
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsVector, 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.nonono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialnonoyes
SQL infoSupport of SQLSQL like support with command line toolnonoyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
RESTful HTTP APIHTTP REST
Java API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
C++
Go
Java
JavaScript (Node.js)
Python
JavaC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersyes, Notifications (with Streaming only)nonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infobased on CassandraShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesnoyes
User concepts infoAccess controlyes (enterprise version only)Role based access control and fine grained access rightsnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BangdbMilvusNewtsSplice Machine
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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BangdbMilvusNewtsSplice Machine
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