DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Bangdb vs. Databricks vs. Pinecone vs. TimesTen

System Properties Comparison Bangdb vs. Databricks vs. Pinecone vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonPinecone  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A managed, cloud-native vector databaseIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Vector 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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitebangdb.comwww.databricks.comwww.pinecone.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.bangdb.comdocs.databricks.comdocs.pinecone.io/­docs/­overviewdocs.oracle.com/­database/­timesten-18.1
DeveloperSachin Sinha, BangDBDatabricksPinecone Systems, IncOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012201320191998
Current releaseBangDB 2.0, October 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinuxhostedhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsString, Number, Booleanyes
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.noyesnono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLnoyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
PythonC
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnouser defined functions and aggregatesPL/SQL
Triggersyes, Notifications (with Streaming only)no
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes infoby means of logfiles and checkpoints
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 modenonoyes
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standard
More information provided by the system vendor
BangdbDatabricksPineconeTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

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
BangdbDatabricksPineconeTimesTen
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Databricks tells investors annualized revenue will reach $2.4 billion at midway point of year
13 June 2024, CNBC

Databricks Launches AI Graphics Competitor to Salesforce, Microsoft
12 June 2024, Yahoo Finance

Legacy data migration to Databricks: Fast transition sitename%%
14 June 2024, SiliconANGLE News

Databricks Data+AI Summit 2024: The Biggest News
12 June 2024, CRN

Why Databricks' Tabular Play Has Put Snowflake On The Defensive
10 June 2024, Forbes

provided by Google 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

Gathr Partners with Pinecone to Accelerate Generative AI Adoption
12 June 2024, ARC Advisory Group

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

provided by Google News



Share this page

Featured Products

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

Milvus logo

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