DBMS > jBASE vs. LeanXcale vs. Postgres-XL vs. TempoIQ vs. Vitess

System Properties Comparison jBASE vs. LeanXcale vs. Postgres-XL vs. TempoIQ vs. Vitess

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A robust multi-value DBMS comprising development tools and middleware

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Multivalue DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.leanxcale.com

www.postgres-xl.org

tempoiq.com (offline)

vitess.io

Technical documentation

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.postgres-xl.org/documentation

vitess.io/docs

Developer

Rocket Software (formerly Zumasys)

LeanXcale

TempoIQ

The Linux Foundation, PlanetScale

Initial release

1991

2015

2014

since 2012, originally named StormDB

2012

2013

Current release

5.7

10 R1, October 2018

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

AIX
Linux
Windows

Linux
macOS

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

yes

through Apache Derby

yes

distributed, parallel query execution

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
Basic
Jabbascript
Java

C
Java
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript

Node.js
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

yes

proprietary syntax

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

MVCC

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

simple authentication-based access control

Users with fine-grained authorization concept

no user groups or roles

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