DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > AlaSQL vs. Amazon Neptune vs. jBASE vs. Kinetica vs. Spark SQL

System Properties Comparison AlaSQL vs. Amazon Neptune vs. jBASE vs. Kinetica vs. Spark SQL

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionJavaScript DBMS libraryFast, reliable graph database built for the cloudA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Graph DBMS
RDF store
Multivalue DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitealasql.orgaws.amazon.com/­neptunewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.comspark.apache.org/­sql
Technical documentationgithub.com/­AlaSQL/­alasqlaws.amazon.com/­neptune/­developer-resourcesdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAndrey Gershun & Mathias R. WulffAmazonRocket Software (formerly Zumasys)KineticaApache Software Foundation
Initial release20142017199120122014
Current release5.77.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT-LicensecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC, C++Scala
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)hostedAIX
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesoptionalyesyes
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.nonoyesnono
Secondary indexesnonoyesno
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.noEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJavaScript APIOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesJavaScriptC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesuser defined functionsno
Triggersyesnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.yesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infoRelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights can be defined down to the item levelAccess rights for users and roles on table levelno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
AlaSQLAmazon NeptunejBASEKineticaSpark SQL
Recent citations in the news

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune | Amazon Web Services
3 June 2024, AWS Blog

AWS Weekly Roundup: LlamaIndex support for Amazon Neptune, force AWS CloudFormation stack deletion, and more ...
27 May 2024, AWS Blog

AWS announces Amazon Neptune I/O-Optimized
22 February 2024, AWS Blog

Amazon Neptune Analytics is now available in the AWS Europe (London) Region
14 March 2024, AWS Blog

Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
29 November 2023, AWS Blog

provided by Google News

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here