DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. GBase vs. Google Cloud Bigtable vs. Ignite vs. TinkerGraph

System Properties Comparison Apache Impala vs. GBase vs. Google Cloud Bigtable vs. Ignite vs. TinkerGraph

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websiteimpala.apache.orgwww.gbase.cncloud.google.com/­bigtableignite.apache.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsapacheignite.readme.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeneral Data Technology Co., Ltd.GoogleApache Software Foundation
Initial release20132004201520152009
Current release4.1.0, June 2022GBase 8a, GBase 8s, GBase 8cApache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, Java, PythonC++, Java, .NetJava
Server operating systemsLinuxLinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesnoyesno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsStandard with numerous extensionsnoANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
ADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBCC#C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoyes (compute grid and cache interceptors can be used instead)no
Triggersnoyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistencynone
Foreign keys infoReferential integritynoyesnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaGBaseGoogle Cloud BigtableIgniteTinkerGraph
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ...
12 October 2023, GlobeNewswire

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

provided by Google News

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune | Amazon Web Services
3 June 2024, AWS Blog

Why developers like Apache TinkerPop, an open source framework for graph computing | Amazon Web Services
27 September 2021, AWS Blog

InfiniteGraph Gets Support for Common Graph Database Language and More
21 February 2012, SiliconANGLE News

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here