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DBMS > Hypertable vs. RocksDB vs. ScyllaDB vs. Splice Machine

System Properties Comparison Hypertable vs. RocksDB vs. ScyllaDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonRocksDB  Xexclude from comparisonScyllaDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Cassandra and DynamoDB compatible wide column storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelWide column storeKey-value storeWide column storeRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#97  Overall
#16  Key-value stores
Score4.15
Rank#69  Overall
#5  Wide column stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiterocksdb.orgwww.scylladb.comsplicemachine.com
Technical documentationgithub.com/­facebook/­rocksdb/­wikidocs.scylladb.comsplicemachine.com/­how-it-works
DeveloperHypertable Inc.Facebook, Inc.ScyllaDBSplice Machine
Initial release2009201320152014
Current release0.9.8.11, March 20169.4.0, June 2024ScyllaDB Open Source 6.0.2, July 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoBSDOpen Source infoOpen Source (AGPL), commercial license 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.
Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageC++C++C++Java
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenonoyesyes
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 indexesrestricted infoonly exact value or prefix value scansnoyes infocluster global secondary indicesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statements (CQL)yes
APIs and other access methodsC++ API
Thrift
C++ API
Java API
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes, Luayes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyesselectable replication factor infoRepresentation of geographical distribution of servers is possibleMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoin-memory tablesyes
User concepts infoAccess controlnonoAccess rights for users can be defined per objectAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
HypertableRocksDBScyllaDBSplice Machine
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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HypertableRocksDBScyllaDBSplice Machine
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