DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Badger vs. Pinecone vs. Splice Machine vs. Yaacomo

System Properties Comparison Badger vs. Pinecone vs. Splice Machine vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonPinecone  Xexclude from comparisonSplice Machine  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A managed, cloud-native vector databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelKey-value storeVector DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.pinecone.iosplicemachine.comyaacomo.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.pinecone.io/­docs/­overviewsplicemachine.com/­how-it-works
DeveloperDGraph LabsPinecone Systems, IncSplice MachineQ2WEB GmbH
Initial release2017201920142009
Current release3.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoString, Number, Booleanyesyes
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 indexesnoyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesGoPythonC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.nonoyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
BadgerPineconeSplice MachineYaacomo
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions
12 June 2024, MarkTechPost

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone launches serverless edition of its vector database on AWS
22 May 2024, SiliconANGLE News

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Splice Machine scores $15M to make Hadoop run in real time
10 February 2014, VentureBeat

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here