DBMS > EJDB vs. GBase vs. Google Cloud Spanner vs. SAP IQ vs. VictoriaMetrics

System Properties Comparison EJDB vs. GBase vs. Google Cloud Spanner vs. SAP IQ vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Columnar RDBMS optimized for Big Data analytics

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store

Relational DBMS

column-oriented

Time Series DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

github.com/Softmotions/ejdb

www.gbase.cn

cloud.google.com/spanner

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

victoriametrics.com

Technical documentation

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

cloud.google.com/spanner/docs

help.sap.com/docs/SAP_IQ

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Softmotions

General Data Technology Co., Ltd.

Google

SAP, formerly Sybase

VictoriaMetrics

Initial release

2012

2004

2017

1994

2018

Current release

GBase 8a, GBase 8s, GBase 8c

16.1 SPS04, April 2019

v1.91, May 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache Version 2.0

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

C, Java, Python

Server operating systems

server-less

Linux

hosted

AIX
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

in-process shared library

ADO.NET
C API
JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication with 3 replicas for regional instances.

SAP/Sybase Replication Server

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

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.

User concepts

Access control

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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