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DBMS > etcd vs. eXtremeDB vs. HarperDB vs. Splice Machine

System Properties Comparison etcd vs. eXtremeDB vs. HarperDB vs. Splice Machine

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHarperDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA distributed reliable key-value storeNatively in-memory DBMS with options for persistency, high-availability and clusteringHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMS
Time Series DBMS
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.05
Rank#53  Overall
#5  Key-value stores
Score0.79
Rank#212  Overall
#100  Relational DBMS
#18  Time Series DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.mcobject.comwww.harperdb.iosplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.mcobject.com/­docs/­extremedb.htmdocs.harperdb.io/­docssplicemachine.com/­how-it-works
DeveloperMcObjectHarperDBSplice Machine
Initial release200120172014
Current release3.4, August 20198.2, 20213.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree community edition 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++Node.jsJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesdynamic schemayes
Typing infopredefined data types such as float or datenoyesyes infoJSON data typesyes
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 infosupport of XML interfaces availableno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes infowith the option: eXtremeSQLSQL-like data manipulation statementsyes
APIs and other access methodsgRPC
JSON over HTTP
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Java
Lua
Python
Scala
.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesCustom Functions infosince release 3.1yes infoJava
Triggersyes, watching key changesyes infoby defining eventsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingA table resides as a whole on one (or more) nodes in a clusterShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Active Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infothe nodes on which a table resides can be definedMulti-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 systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlnoAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard

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