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 > BigchainDB vs. Hawkular Metrics vs. HEAVY.AI vs. Spark SQL

System Properties Comparison BigchainDB vs. Hawkular Metrics vs. HEAVY.AI vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.bigchaindb.comwww.hawkular.orggithub.com/­heavyai/­heavydb
www.heavy.ai
spark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.heavy.aispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCommunity supported by Red HatHEAVY.AI, Inc.Apache Software Foundation
Initial release2016201420162014
Current release5.10, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0
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 languagePythonJavaC++ and CUDAScala
Server operating systemsLinuxLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnonono
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
HTTP RESTJDBC
ODBC
Thrift
Vega
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
Go
Java
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandraMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardno

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
BigchainDBHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Spark SQL
Recent citations in the news

Exploring the 10 BEST Python Libraries for Blockchain Applications
9 September 2023, DataDrivenInvestor

An Introduction to BigchainDB, a Popular Blockchain Database
17 September 2020, Open Source For You

Blockchain Database Startup BigchainDB Raises €3 Million
27 September 2016, CoinDesk

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

What is BigchainDB Technology & How it works and the Characteristics?
26 August 2017, Blockchain Council

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

HEAVY.AI Introduces HeavyIQ, Delivering Powerful Conversational Analytics Focused on Location and Time Data
19 March 2024, Datanami

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB 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.

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Present your product here