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DBMS > HarperDB vs. Sadas Engine vs. Spark SQL vs. Teradata Aster

System Properties Comparison HarperDB vs. Sadas Engine vs. Spark SQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionUltra-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.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#244  Overall
#38  Document stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.harperdb.iowww.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.harperdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHarperDBSADAS s.r.l.Apache Software FoundationTeradata
Initial release2017200620142005
Current release3.1, August 20218.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infofree trial version availableOpen Source infoApache 2.0commercial
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 languageNode.jsC++Scala
Server operating systemsLinux
OS X
AIX
Linux
Windows
Linux
OS X
Windows
Linux
Data schemedynamic schemayesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes infoJSON data typesyesyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like data manipulation statementsyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
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
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1nonoR packages
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioningyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definednonenoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
HarperDBSadas EngineSpark SQLTeradata Aster
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