DBMS > EJDB vs. GreptimeDB vs. Manticore Search vs. Newts vs. Splice Machine

System Properties Comparison EJDB vs. GreptimeDB vs. Manticore Search vs. Newts vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Multi-storage database for search, including full-text search.

Time Series DBMS based on Cassandra

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

github.com/Softmotions/ejdb

greptime.com

manticoresearch.com

opennms.github.io/newts

splicemachine.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.greptime.com

manual.manticoresearch.com

github.com/OpenNMS/newts/wiki

splicemachine.com/how-it-works

Developer

Softmotions

Greptime Inc.

Manticore Software

OpenNMS Group

Splice Machine

Initial release

2012

2022

2017

2014

Current release

6.0, February 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

GPL version 2

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

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

Rust

C++

Java

Server operating systems

server-less

Android
Docker
FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

schema-free, schema definition possible

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

in-process shared library

gRPC
HTTP API
JDBC

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

HTTP REST
Java API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Erlang
Go
Java
JavaScript

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

Python

user defined functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

based on Cassandra

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Access rights for users, groups and roles 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.

Related products and services

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