DBMS > AlaSQL vs. Ehcache vs. GreptimeDB vs. Hawkular Metrics vs. TimescaleDB

System Properties Comparison AlaSQL vs. Ehcache vs. GreptimeDB vs. Hawkular Metrics vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A widely adopted Java cache with tiered storage options

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

www.ehcache.org/documentation

docs.greptime.com

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.timescale.com

Developer

Andrey Gershun & Mathias R. Wulff

Terracotta Inc, owned by Software AG

Greptime Inc.

Community supported by Red Hat

Timescale

Initial release

2014

2009

2022

2014

2017

Current release

3.10.0, March 2022

2.15.0, May 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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

JavaScript

Java

Rust

Java

Server operating systems

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

All OS with a Java VM

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

full PostgreSQL SQL syntax

APIs and other access methods

JavaScript API

JCache

gRPC
HTTP API
JDBC

HTTP REST

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

Supported programming languages

JavaScript

Java

C++
Erlang
Go
Java
JavaScript

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Python

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

based on Cassandra

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

selectable replication factor

based on Cassandra

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

using a tiered cache-storage approach

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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