DBMS > LeanXcale vs. Prometheus vs. TimesTen vs. XTDB

System Properties Comparison LeanXcale vs. Prometheus vs. TimesTen vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

Open-source Time Series DBMS and monitoring system

In-Memory RDBMS compatible to Oracle

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store

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	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.leanxcale.com

prometheus.io

www.oracle.com/database/technologies/related/timesten.html

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

prometheus.io/docs

docs.oracle.com/database/timesten-18.1

www.xtdb.com/docs

Developer

LeanXcale

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Juxt Ltd.

Initial release

2015

1998

2019

Current release

11 Release 2 (11.2.2.8.0)

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Clojure

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

Numeric data only

yes

yes, extensible-data-notation format

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST
JDBC

Supported programming languages

C
Java
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Java
PL/SQL

Clojure
Java

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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