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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Graph Engine vs. ObjectBox

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Graph Engine vs. ObjectBox

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors
Primary database modelRelational DBMSKey-value store
Wide column store
Graph DBMS
Key-value store
Object oriented DBMS
Vector DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.graphengine.iogithub.com/­objectbox
objectbox.io
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.objectbox.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftObjectBox Limited
Initial release2013201520102017
Current release4.1.0, June 20224.0 (May 2024)
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoMIT LicenseBindings are released under Apache 2.0 infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++.NET and CC and C++
Server operating systemsLinuxhosted.NETAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes, plus "flex" map-like types
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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonono
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIProprietary native API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesData sync between devices allowing occasional connected databases to work completely offline
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
Apache ImpalaGoogle Cloud BigtableGraph Engine infoformer name: TrinityObjectBox
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More resources
Apache ImpalaGoogle Cloud BigtableGraph Engine infoformer name: TrinityObjectBox
Recent citations in the news

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
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Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
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31 January 2022, InfoQ.com

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

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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

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Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

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ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

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