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DBMS > HEAVY.AI vs. Hypertable vs. IBM Db2 Event Store vs. Solr

System Properties Comparison HEAVY.AI vs. Hypertable vs. IBM Db2 Event Store vs. Solr

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHypertable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSolr  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn open source BigTable implementation based on distributed file systems such as HadoopDistributed Event Store optimized for Internet of Things use casesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSWide column storeEvent Store
Time Series DBMS
Search engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­db2-event-storesolr.apache.org
Technical documentationdocs.heavy.aiwww.ibm.com/­docs/­en/­db2-event-storesolr.apache.org/­resources.html
DeveloperHEAVY.AI, Inc.Hypertable Inc.IBMApache Software Foundation
Initial release2016200920172006
Current release5.10, January 20220.9.8.11, March 20162.09.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license availablecommercial infofree developer edition availableOpen Source infoApache Version 2
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 languageC++ and CUDAC++C and C++Java
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoLinux, macOS, Windows for the developer additionAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes infosupports customizable data types and automatic typing
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
Secondary indexesnorestricted infoonly exact value or prefix value scansnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoyes infothrough the embedded Spark runtimeSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Thrift
Vega
C++ API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyesJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factor on file system levelActive-active shard replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardyes

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HypertableIBM Db2 Event StoreSolr
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