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DBMS > Heroic vs. IBM Db2 Event Store vs. Sphinx vs. Splice Machine

System Properties Comparison Heroic vs. IBM Db2 Event Store vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchDistributed Event Store optimized for Internet of Things use casesOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSEvent Store
Time Series DBMS
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.ibm.com/­products/­db2-event-storesphinxsearch.comsplicemachine.com
Technical documentationspotify.github.io/­heroicwww.ibm.com/­docs/­en/­db2-event-storesphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperSpotifyIBMSphinx Technologies Inc.Splice Machine
Initial release2014201720012014
Current release2.03.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree developer edition availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++Java
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nono
Secondary indexesyes infovia Elasticsearchnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimeSQL-like query language (SphinxQL)yes
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive-active shard replicationnoneMulti-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 systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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HeroicIBM Db2 Event StoreSphinxSplice Machine
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