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DBMS > atoti vs. HarperDB vs. Lovefield vs. Sphinx vs. Splice Machine

System Properties Comparison atoti vs. HarperDB vs. Lovefield vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHarperDB  Xexclude from comparisonLovefield  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Embeddable relational database for web apps written in pure JavaScriptOpen 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 modelObject oriented DBMSDocument storeRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteatoti.iowww.harperdb.iogoogle.github.io/­lovefieldsphinxsearch.comsplicemachine.com
Technical documentationdocs.atoti.iodocs.harperdb.io/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperActiveViamHarperDBGoogleSphinx Technologies Inc.Splice Machine
Initial release2017201420012014
Current release3.1, August 20212.1.12, February 20173.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree versions availablecommercial infofree community edition availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaNode.jsJavaScriptC++Java
Server operating systemsLinux
OS X
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemedynamic schemayesyesyes
Typing infopredefined data types such as float or dateyes infoJSON data typesyesnoyes
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 indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like data manipulation statementsSQL-like query language infovia JavaScript builder patternSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
JavaScriptC++ 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 proceduresPythonCustom Functions infosince release 3.1nonoyes infoJava
TriggersnoUsing read-only observersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningA table resides as a whole on one (or more) nodes in a clusternoneSharding 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 nodesyes infothe nodes on which a table resides can be definednonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, using LMDByes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes 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.yesyesyes infousing MemoryDByes
User concepts infoAccess controlAccess rights for users and rolesnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
atotiHarperDBLovefieldSphinxSplice Machine
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