DBMS > Adabas vs. EsgynDB vs. KeyDB vs. Lovefield vs. Splice Machine

System Properties Comparison Adabas vs. EsgynDB vs. KeyDB vs. Lovefield vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

www.esgyn.cn

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

splicemachine.com

Technical documentation

docs.keydb.dev

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

splicemachine.com/how-it-works

Developer

Software AG

Esgyn

EQ Alpha Technology Ltd.

Google

Splice Machine

Initial release

1971

2015

2019

2014

Current release

2.1.12, February 2017

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

BSD-3

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

C++, Java

C++

JavaScript

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

ADO.NET
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Natural

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

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

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

Lua

yes

Java

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

fine grained access rights according to SQL-standard

simple password-based access control and ACL

Access rights for users, groups and roles according to SQL-standard

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