DBMS > GeoSpock vs. LeanXcale vs. Lovefield vs. SAP HANA

System Properties Comparison GeoSpock vs. LeanXcale vs. Lovefield vs. SAP HANA

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Embeddable relational database for web apps written in pure JavaScript

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

geospock.com

www.leanxcale.com

google.github.io/lovefield

www.sap.com/products/hana.html

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

help.sap.com/hana

Developer

GeoSpock

LeanXcale

Google

SAP

Initial release

2015

2014

2010

Current release

2.0, September 2019

2.1.12, February 2017

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

JavaScript

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Appliance or cloud-service

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

through Apache Derby

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

Supported programming languages

C
Java
Scala

JavaScript

Server-side scripts

Stored procedures

SQLScript, R

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users can be defined per table

yes

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